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MTF Supply & Demand Zones [ZeroEmotionTrading]**MTF Supply & Demand Zones ** is a multi-timeframe market structure tool that maps where aggressive buying and selling has historically entered the market, then ranks those zones by strength, tracks how price interacts with them in real time, and converts that information into a tactical dashboard for trade decision-making.
Instead of showing a single support or resistance level, this indicator builds a full **multi-timeframe supply/demand map**, scores the importance of each active zone, measures whether buyers or sellers are winning the battle inside those zones, and helps identify whether price is more likely to **bounce, continue, weaken, or break through**.
It is designed to answer three questions quickly:
1. **Who is in control right now?**
2. **Is the current floor/ceiling strong or failing?**
3. **Is there enough confluence to justify a trade?**
---
## Detailed Explanation of Features
### 1) Multi-Timeframe Supply & Demand Zones
The core of the indicator is the zone engine.
* **Blue Zones = Demand**
Areas where strong buying previously entered the market. Think of these as potential floors.
* **Orange Zones = Supply**
Areas where strong selling previously entered the market. Think of these as potential ceilings.
The indicator monitors multiple timeframes at once so you can see:
* local reaction zones
* lower timeframe scalp zones
* higher timeframe structural zones
This helps separate weak intraday levels from meaningful macro areas.
---
### 2) Zone Ranking System
Each active zone is ranked by relative strength.
* **#1 zones** are the strongest and most important active zones
* lower-ranked zones provide context and secondary reaction areas
* muted “ghost” zones help visualize broader structure without overpowering the chart
A high-rank zone matters more than a low-rank zone, especially when price is approaching it for the first time.
---
### 3) Zone Labels and Battle Bars
Each zone label shows:
** | | **
The battle bar is one of the most important parts of the system because it shows what is happening **inside the zone after creation**.
* **White blocks** = virgin zone
Price has not meaningfully interacted with it since creation. These are often the cleanest reaction zones.
* **Blue blocks** = buying pressure inside the zone
* **Orange blocks** = selling pressure inside the zone
This lets you read whether a zone is still healthy or under attack.
Examples:
* A **blue demand zone filling with orange blocks** means sellers are pressing into the floor
* An **orange supply zone filling with blue blocks** means buyers are leaning on the ceiling
* A heavily imbalanced battle bar often warns that a zone may fail soon
---
### 4) Dashboard / Tactical Console
The dashboard turns raw zone data into a real-time market read.
#### Overall Bias
A 0–100 weighted bias meter showing bullish vs bearish confluence from all active zones.
* **Higher values** favor bullish conditions
* **Lower values** favor bearish conditions
* It is proximity-weighted, so zones close to price matter more than zones far away
This is your broad “which side has the edge” read.
---
#### Logic Signal
This tells you the current condition of the market structure.
Common states include:
* **Stable**
Current structure is intact and there is no immediate warning
* **Zone Weakening**
Price is pushing deep into a zone and the level is losing integrity
* **Barrier Critical**
Price is near or beyond the critical break point of the current floor/ceiling
* **Vacuum Creep**
Price is drifting without fresh structural creation and may move inefficiently until it finds the next major zone
This is one of the best ways to know whether you should trust a level or expect failure.
---
#### Max Penetration
Shows how deeply price has pushed into a zone.
* low penetration usually means the level is reacting cleanly
* high penetration means the zone is being stress-tested
* extreme penetration often warns of likely breakdown or breakout
This is critical for avoiding “buying a floor that is already failing” or “shorting a ceiling that is already being absorbed.”
---
#### Price Driver
Identifies the immediate force affecting price.
Examples:
* **Driven by Demand**
* **Driven by Supply**
* **Scanning Market** when no clear driver is dominant
This is the short-term controller and helps with timing entries and understanding whether price is reacting to a live floor or ceiling.
---
#### Market Trend / Regime
This gives the broader condition of the tape.
Examples may include:
* bullish bias
* bearish bias
* bullish breakout
* sideways
* choppy
This helps distinguish between:
* clean directional conditions
* breakout conditions
* messy/noisy environments where selectivity matters more
---
#### Bars Since Demand / Structural Recency
Shows how long it has been since a new meaningful zone event occurred.
This helps identify whether the market is:
* still being supported by fresh structure
* or drifting away from recent zone formation
---
#### Scorecard
A fast summary of bullish vs bearish zone influence.
This is useful for quickly checking whether the market currently favors:
* demand-led structure
* supply-led structure
* or mixed conditions
---
#### Power Balance
A visual barometer of aggregated zone pressure.
This gives you a quick read on whether active market structure is dominated by buyers or sellers.
---
#### Latest Area
Displays the most relevant newly active zone around current price.
This is useful for understanding what the market is currently reacting to.
---
#### Zone Stack
Shows when multiple timeframes overlap in the same area.
This is extremely important.
A stack means:
* multiple zones from different timeframes are aligned in the same region
* the level usually carries more weight
* the reaction potential is often stronger than a single isolated zone
Stacked zones are some of the highest-quality areas on the chart.
---
### 5) Lower Dashboard / Per-Timeframe Readout
The lower left panel breaks down the individual timeframe state.
Depending on your version, it may include metrics such as:
* EMA alignment
* structural confirmation
* volume delta / VIDYA-based bias
* volume transition
* volume strength
This is where you can see whether lower timeframes and higher timeframes are aligned or diverging.
When several rows point in the same direction, trade quality improves.
---
### 6) Entry / Rejection Markers
The system can also display trade triggers or reaction markers when price interacts with zones.
Typical use:
* bullish confirmation when demand holds
* bearish confirmation when supply rejects
* optional management / exit-style prompts depending on your settings
These markers are not meant to replace context. They work best when aligned with the dashboard and zone structure.
---
## How to Trade the Indicator
The indicator is built around three core trade ideas.
---
### Play A: High-Confluence Reversal
This is the classic reversal off a strong floor or ceiling.
#### Long example
* price drops into a **stacked demand area**
* dashboard bias improves
* price driver shifts toward demand
* battle bar shows the zone is not being overwhelmed
* bullish confirmation appears
Entry:
* on the rejection candle close or confirmation marker
Stop:
* below the structural low of the stacked demand area
Target:
* nearest opposing supply
* then higher timeframe supply if momentum continues
#### Short example
Same logic in reverse at stacked supply.
Best use:
* when a major floor/ceiling is being defended
* when there is visible multi-timeframe confluence
---
### Play B: Trend Continuation Pullback
This is the bread-and-butter continuation trade.
#### Bullish continuation
* overall bias is bullish
* demand is dominant on the scorecard / power balance
* price pulls back into a fresh or lightly tested blue zone
* rejection confirms the level
Entry:
* on the bounce / confirmation candle close
Stop:
* below the supporting demand zone
Target:
* retest of recent highs
* then the next supply zone above
#### Bearish continuation
Reverse the process:
* bearish bias
* supply in control
* price pulls back into orange
* rejection confirms
This play works best when trading **with** the dominant structure instead of fading it.
---
### Play C: Zone Failure / Breakout
This is the “do not fade the level” setup.
Use this when:
* logic shifts to **Barrier Critical**
* max penetration is high
* battle bars show the defending side is losing
* price closes through the level with acceptance
#### Bullish breakout
* supply is absorbed
* price accepts above the ceiling
* old supply can become support on retest
#### Bearish breakdown
* demand is overrun
* price closes below the floor
* old demand can become resistance on retest
The key is not just the break itself, but whether price **accepts** beyond the zone.
---
## Practical Trading Workflow
A simple process for reading the indicator:
### Step 1: Identify the Controller
Check:
* Overall Bias
* Price Driver
* Power Balance
* Market Trend
This tells you whether the market is currently demand-led, supply-led, or mixed.
---
### Step 2: Evaluate the Zone
Before taking any entry, ask:
* is the zone virgin or already heavily tested?
* is it high-rank or low-rank?
* is it stacked with other timeframes?
* is it being defended or attacked?
Not all zones are equal.
---
### Step 3: Check Penetration
A clean reaction is very different from a zone that is already nearly broken.
* shallow penetration = healthier reaction
* deep penetration = caution
* extreme penetration = prepare for failure / breakout conditions
---
### Step 4: Wait for Confirmation
The highest-probability setups happen when:
* the dashboard agrees
* the zone quality is strong
* the controller is aligned
* a rejection / continuation trigger appears
This keeps you from trading every touch blindly.
---
### Step 5: Manage the Trade by Structure
For longs:
* stay valid while price holds above demand
* reduce if price loses the zone cleanly
For shorts:
* stay valid while price remains capped below supply
* reduce if price reclaims the zone with acceptance
Targets are usually:
* first opposing zone
* then the next higher-timeframe zone if momentum continues
---
## Best Use Cases
This indicator is best suited for traders who want to:
* trade supply and demand with more context
* combine structure, pressure, and confluence into one system
* avoid taking low-quality reactions from weak zones
* distinguish between bounce conditions and breakout conditions
It can be used for:
* intraday trading
* scalp execution
* swing context
* top-down confluence planning
---
## Key Interpretation Rules
A few simple rules improve results significantly:
* **Virgin zones are stronger than heavily tested zones**
* **Stacked zones are stronger than isolated zones**
* **High penetration weakens a zone**
* **A zone under siege should not be trusted blindly**
* **Trade confirmations work best when aligned with the dashboard**
* **Breaks matter less than acceptance beyond the zone**
* **Do not fight strong higher-timeframe confluence without clear failure evidence**
---
## Final Note
This indicator is designed to help traders make more objective decisions by reading where the market is likely to react, weaken, or break. It is not just a support/resistance tool, but a **multi-timeframe tactical decision framework** built around live zone strength, directional control, and structural confluence.
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A1 Value Turn Triple Mode v2.3 (Swing + Crypto)# A1 Value Turn Triple Mode v2.3 — Swing + Crypto
## Overview
The A1 Value Turn is a multi-layer confluence indicator designed to identify high-probability mean reversion entries on quality stocks and crypto assets that have pulled back significantly from their 52-week highs. It combines value band detection, moving average proximity, RSI momentum, volume confirmation, sector rotation, and IV rank filtering into a single signal system with a built-in 3-leg exit ladder.
Built for swing traders and options traders targeting 60–90 DTE calls or verticals on A-grade companies trading at a discount.
---
## How It Works
### 4-Layer Signal Gate
A full signal only fires when ALL four conditions align:
1. **Value Band** — Price is 40–60% (or 60–80% in Deep mode) below its 52-week high
2. **MA Proximity** — Price is within a configurable % of the 200-period SMA
3. **RSI Turn** — RSI is within the mode-specific range AND curling upward from the prior bar
4. **Volume Surge** — Current volume is at least 1.3x the 20-day average
Plus two optional confirmation layers:
- **Sector ETF confirmation** — The selected sector ETF RSI is also curling up and price is above its 50 MA
- **IV Rank filter** — Historical volatility rank is below your threshold, ensuring you are not overpaying for options premium
---
## Three Modes
| Mode | Value Band | RSI Range | Vol Mult | Target 1 |
|---|---|---|---|---|
| 40–60% off High (Swing) | 40–60% below 52W high | 40–70 | 1.3x | +20% |
| 60–80% off High (Deep) | 60–80% below 52W high | 35–70 | 1.3x | +35% |
| Crypto-Linked | Any | 25–75 | 1.1x | +50% |
---
## 3-Leg Exit Ladder
Every signal automatically calculates three exit targets with live R:R ratios:
- **Target 1** — Mode-specific % gain from entry (scale out 1/3)
- **Target 2** — 2x Target 1 (scale out 1/3)
- **Target 3** — The actual 52-week high (full recovery, scale out final 1/3)
Each target plots as a dashed horizontal line anchored to the signal bar. The ATR-based stop loss plots simultaneously so you know your risk before you enter.
---
## Signal States on the Chart
| Shape | Color | Meaning |
|---|---|---|
| Large triangle below bar | Mode color (aqua/orange/purple) | All layers confirmed — entry signal |
| Small triangle below bar | Faded orange | Stock + sector ready, IV rank too high — wait |
| Small triangle below bar | Faded gray | Stock + IV ready, sector not confirmed — wait |
| Gold circle above bar | Yellow | Bullish RSI divergence confluence bonus |
| Bar background tint | Mode color | Full signal bar highlight |
---
## Signal Label
Each confirmed signal prints a label showing:
- Entry price
- Target 1, 2, and 3 with % gain and R:R ratio per leg
- ATR stop loss price
- HV Rank % and current VIX reading
- Sector ETF RSI
- % off 52-week high, RSI, and volume ratio
---
## IV Rank Filter (New in v2.3)
Since PulseWire does not provide live options IV data in Pine Script, this indicator uses Historical Volatility Rank — the annualized standard deviation of daily log returns measured against its own 52-week high and low range. HV Rank and IV move together closely enough that HV Rank is the standard professional proxy used in Pine-based systems.
A separate VIX macro threshold adds a second layer — if the market fear index is above your set level, signals are suppressed regardless of individual stock HV.
When IV is too high, a pending orange triangle fires with a label showing exactly what threshold to wait for.
---
## Inputs
### Core Settings
- Lookback for 52W High (bars)
- Long MA Length
- RSI Length
- Max % Distance from MA
- Mode selection
### Display
- Show/hide table, labels, stop line, Target 2, Target 3
- ATR Length and Multiplier for stop calculation
### IV Rank Filter
- Enable/disable IV filter
- Max HV Rank % (default 50)
- Enable/disable VIX threshold
- Max VIX level (default 25)
### Sector Rotation
- Enable/disable sector confirmation
- Sector ETF ticker (XLK, XLV, XLF, XLY, etc.)
- Sector ETF MA length
---
## Alerts
Four alert conditions built in:
1. **Full Signal** — All layers confirmed, ready to enter
2. **Pending IV** — Stock and sector ready, waiting for IV to cool
3. **Pending Sector** — Stock and IV ready, waiting for sector confirmation
4. **Max Confluence** — Full signal AND bullish RSI divergence
---
## Recommended Use
1. Run a Finviz scan each morning filtering for large caps 40–80% off their 52-week high with above-average volume
2. Open each candidate in PulseWire with this indicator applied
3. Set your sector ETF to match the stock's sector
4. Wait for a full signal (large colored triangle)
5. Use the label to size your 60–90 DTE options position using the printed R:R ratios
6. Scale out 1/3 at each target
Best results on daily timeframe. Works on weekly for longer-horizon setups.
---
## Notes
- This indicator is for educational and informational purposes
- Past signals do not guarantee future results
- Always use proper position sizing and risk management
- HV Rank is a proxy for IV, not actual options implied volatility
---
*Built by MOR Trading Systems* Indicator
Compounding Growth Tracker (Daily)📊 Compounding Growth Tracker (Daily) — Full Description
🧾 Overview
The Compounding Growth Tracker (Daily) is a Pine Script v6 PulseWire indicator designed to visualize and track the exponential growth of a starting capital through daily compounding returns over a 12-month trading period. It combines a live growth curve plot, a target profit line, and an interactive weekly breakdown table — all configurable through simple input parameters.
🎯 Purpose
This tool is built for traders who operate with a fixed daily profit target (e.g., 10% per day) and want to:
📈 See exactly how their account compounds day by day
🗓️ Track progress week by week within any selected month
🏁 Know when they'll hit a financial target (e.g., $1,000,000)
🧠 Stay motivated and disciplined with a visual growth roadmap
⚙️ Input Parameters
Parameter Default Description
Starting Capital ($) $4,000 The initial account balance to compound from
Daily Interest Rate (%) 10% The fixed daily return percentage applied each trading day
Target Amount ($) $1,000,000 The profit goal displayed as a dashed horizontal line
Show Month (1–12) 1 Selects which month's weekly breakdown to display in the table
📐 How It Works
The core formula driving the entire indicator is the compound interest formula:
Future Value = P × (1 + r)ⁿ
Where:
P = Starting Capital
r = Daily Rate (as a decimal)
n = Number of trading days elapsed
The indicator assumes:
5 trading days per week
4 weeks per month
20 trading days per month
240 trading days across 12 months
📊 Visual Components
1. 📈 Growth Curve (Lime Line)
Plots the compounded account value across the first 240 bars of the chart
Grows exponentially, visually demonstrating the power of compounding
Color: Bright Lime Green for high visibility
2. 🎯 Target Line (Yellow Dashed)
A horizontal dashed line marking your financial target
Serves as a constant visual reminder of the end goal
Labeled with a 🎯 emoji for instant recognition
3. 📋 Weekly Breakdown Table (Top Right)
Displayed in a 7-column × 6-row table in the top-right corner of the chart:
Column Content
Week Week number (1–4)
Day 1–2 Balance after Day 1 and Day 2 (Aqua)
Day 3–4 Balance after Day 3 and Day 4 (Lime)
Day 5 End-of-week balance (Yellow)
Wk End Final balance for the week (Yellow)
The TOTAL row at the bottom shows the month-end balance and the growth multiplier (e.g., 6.7×)
Color-coded rows alternate between two shades of blue for readability
The selected month is displayed in the header cell
🎨 Color Coding Guide
Color Meaning
🟢 Lime Growth curve / Mid-week values (Day 3–4)
🔵 Aqua Early-week values (Day 1–2)
🟡 Yellow End-of-week values / Growth multiplier
🟣 Fuchsia Month-end total balance
🔴 Yellow Dashed Target amount line
🟦 Navy Table header background
🟣 Purple Monthly total row background
💡 Use Case Example
Starting with $4,000 at 10% daily over 20 trading days (Month 1):
Day Balance
Day 1 $4,400
Day 5 $6,442
Day 10 $10,375
Day 20 $26,909
Month 6 End ~$304,000
Month 12 End ~$2.2 Billion
⚠️ Important Notes
This indicator is purely mathematical — it does not use real market data for calculations
The growth curve is mapped to bar index, not calendar dates, so it aligns to the first 240 bars on any chart
Best applied on a custom/synthetic ticker or used purely as a planning and motivation tool
A 10% daily return is an extremely aggressive assumption — use responsibly for goal visualization only
🔮 Ideal For
💹 Prop firm traders building a scaling plan
🤖 Algorithmic traders projecting bot performance
📚 Trading educators demonstrating compound growth
🧮 Financial planners visualizing aggressive growth scenarios
🎯 Goal-driven traders who need a daily visual target to stay on track Indicator
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Intuitive Trade Regime [TraderZen]The 3D Geometry of Momentum.
Try this on your favorite chart! Every trader thinks in images. We say the market "took a turn," that price is "going sideways" .. that a breakout "jumped over resistance." We describe a selloff as a "cliff drop" and a rally as a "rapid rise." We watch price "bounce off support" or "breach the borders" of a range. These are not casual metaphors — they are how the mind actually processes price action.
This indicator is built for that visual mind. It translates the structure of price movement into shapes that feel familiar — not because they have been studied, but because they have been seen. The goal is not to add more data to the chart. It is to make what is already there easier to perceive.
The Staircase
Price does not move in lines. It moves in segments — rises and flats, drops and pauses. In structure, this is no different from a staircase. Each trend segment is a step, and the shape of that step tells a story.
The tread — the horizontal span — shows how long a regime held. A wide tread means price spent time consolidating before the next move. A narrow one means momentum carried through without pause.
The riser — the vertical face between steps — shows the magnitude of the shift. A tall riser marks a decisive regime change. A short one marks a continuation, a nudge in the same direction.
The landing — a wider, flatter segment — appears when the market pauses to establish a range before committing. It is the moment between moves where direction has not yet been decided.
And the nosing — the overshoot at each edge — reveals how aggressively price tested the boundary before accepting it.
When these elements are narrow and steep, the staircase is rickety — momentum is high but potentially unstable. When they are wide and gradual, the staircase is solid — a measured, deliberate trend. When they alternate in size, the staircase is winding — a market searching for direction.
This is not a metaphor layered onto the chart. It is what the channel segments actually form. The indicator simply makes the staircase visible.
Perspective as Information
One of the more unusual features of this indicator is its use of 3D depth — not for decoration, but for orientation.
In a downward move, the depth faces project upward and behind, as if you are standing above and looking down at the price descending below you. The top surface of each segment is visible. You see where price came from.
In an upward move, the depth reverses. The faces project downward and forward, as if you are looking up at a structure rising above you. The underside of each segment is exposed. You see the climb from below.
This is not arbitrary. It mirrors how we naturally perceive direction. Looking down implies a fall. Looking up implies a rise. The perspective reinforces the regime — making it something you feel, not just something you read from a label.
The direction of depth is fully configurable, with independent control for bull and bear segments. But the defaults are set to match this natural orientation: upward moves seen from below, downward moves seen from above.
Compression and Expansion
The width of the channel adapts to volatility. When the channel tightens, price is compressing — energy is building. When it widens, expansion is underway — the move is in progress.
In tight bear segments, the depth face breaks into a cascading waterfall pattern — stepped terraces that descend like water over ledges. This is not cosmetic. Narrow bear channels often represent rapid, liquidation-driven moves, and the waterfall texture makes that character immediately visible.
In tight bull segments, the depth face becomes jagged — an ascending cliff with rough, uneven edges. Narrow bull channels often reflect sharp, momentum-driven rallies, and the rocky texture communicates that energy at a glance.
These effects activate automatically when the channel compresses below a configurable threshold relative to ATR. When the channel is wide, the faces remain smooth and clean.
What the Channel Tells You
The mid line is the structural anchor. In Lead mode, it sits on the opposite side of price — acting as support in uptrends and resistance in downtrends, decaying slowly away from price like a trailing reference. In Follow mode, it tracks toward price, blending with the local basis.
The bands define the expected range. Price staying within the bands confirms the current regime. A confirmed break beyond the band triggers a regime change — marked by a triangle on the chart.
Retests occur when price touches the far band without conviction. These are marked with smaller arrows and often represent pullback entries within the trend.
Continuation steps fire when price pushes further in the current direction, extending the trend. Refresh events occur when a segment has aged out or drifted too far from the local basis — the channel quietly re-anchors without changing direction.
Each of these events reshapes the staircase. A regime flip starts a new step. A continuation extends the current one. A refresh adjusts the footing without changing the path.
Themes
The indicator ships with preset visual themes that configure the gradient, transparency, and 3D settings as a group:
Classic — Clean channel with gradient fills. No 3D effects. The original look for those who prefer simplicity.
Price Slabs — Solid 3D segments with depth and perspective. The staircase made tangible. Waterfall and cliff effects enabled.
Neon Glass — Translucent 3D segments with a lighter touch. The structure is visible but does not dominate the chart.
Custom — Full control over every parameter. Build your own visual language.
All themes respect your chosen colors. Switching themes changes the structure and feel — not the palette.
A Note on Design Philosophy
Most indicators ask the trader to interpret numbers. This one asks the trader to observe shapes. The thesis is simple: if the visual representation is honest — if the shapes genuinely correspond to the character of the move — then pattern recognition does what it has always done. The trader sees what is happening, and the chart stops being a puzzle to decode.
The 3D effects, the staircase structure, the perspective shifts — these are not aesthetic choices. They are attempts to give price action a physical presence on the chart, so that reading a trend feels less like analyzing data and more like watching something move.
That is what intuitive means here. Not simplified. Not dumbed down. Just shaped for the way the eye already works.
Disclaimer
This indicator is a visual analysis tool designed to aid in the interpretation of price action. It does not generate buy or sell signals, and nothing presented here constitutes financial advice, a trading recommendation, or a solicitation to trade any financial instrument. Past visual patterns do not guarantee future price behavior. All trading involves risk, including the potential loss of principal. Users are solely responsible for their own trading decisions and should consult a qualified financial advisor before acting on any information derived from this or any other technical tool. The author assumes no liability for any losses incurred through the use of this indicator.
Built by TraderZen
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Performance Comparison (Zeiierman)█ Overview
Performance Comparison (Zeiierman) is a period-mapping comparison engine that shows how the current month, quarter, or year is evolving relative to its historical structure.
It takes completed historical periods, compresses each into a normalized timeline, and overlays them on the active period so you can compare paths, pace, expansion, and finish. Instead of only asking where the price is now, the script asks how this period is behaving relative to past periods at the same stage of development.
The indicator displays all curves in Percentage Accumulated terms, meaning each period starts at the same zero point and then tracks total return from that period start. This makes it easier to compare period structure on an equal footing, regardless of the asset’s raw price level.
█ How It Works
⚪ 1) Period Segmentation
The script groups price into repeating time buckets based on the selected Period:
Monthly
Quarterly
Yearly
Each new month, quarter, or year starts a fresh period, while completed periods are stored for later comparison.
⚪ 2) Timeline Normalization
Because historical periods do not all contain the same number of bars, each is remapped to a shared normalized progress scale from start to end.
This allows the script to compare:
the beginning of one period to the beginning of another
the midpoint of one period to the midpoint of another
the final stage of one period to the final stage of another
So even if one quarter had more bars than another, both can still be compared on the same visual path.
⚪ 3) Value Mapping
The script uses Percentage Accumulated only.
Each period begins at 0% and then tracks cumulative return from that period’s starting price:
Percentage Accumulated = current price/period starting price − 1
This means all periods are anchored to the same starting point, making relative path comparison much cleaner than raw price comparison.
⚪ 4) Historical Curve Engine
Completed periods are collected into comparison buckets across the normalized timeline. From these buckets, the script can draw:
Historical paths
Median path
Average path
This creates a period-based structure model rather than a simple price overlay.
⚪ 5) Current Period Tracking
The active period is plotted on top of the historical framework, so you can see:
whether the current action is stronger or weaker than normal
whether it is tracking near the median path
whether it is diverging from the average or historical range
where the current period sits in time through the timeline bar
⚪ 6) Similarity Table
The table compares the current period against past visible periods using four path metrics:
MAE: Average distance from the current path. Lower is better.
Max Dev: Largest divergence at any point. Lower is better.
Dir Match %: How often did both paths move in the same direction? Higher is better.
End Diff: Difference at the latest comparable point. Closer to zero is better.
This helps identify which historical period most closely resembles the current one.
█ Why It Is Useful
⚪ Structural Context
The script does not just show whether the price is up or down. It shows whether the current period is unfolding in a way that is typical, weak, extended, delayed, or abnormal relative to history.
⚪ Period-Based Comparison
It is especially useful for traders and analysts who think in recurring cycles, such as:
monthly structure
quarterly seasonality
yearly progression
█ How to Use
⚪ Historical Comparison
Use the historical paths to see how prior periods behaved across the full normalized timeline.
⚪ Median Path
Use the median as the most typical historical path. This is often the cleanest benchmark for “normal” behavior.
⚪ Average Path
Use the average to measure the broad mean tendency of past periods.
⚪ Current Period
Use the current path to judge whether the live period is:
leading
lagging
tracking normally
diverging sharply from history
⚪ Similarity Table
Use the table to find the closest historical analog to the current period.
Low MAE and Max Dev suggest close path similarity.
High Dir Match % suggests similar movement behavior.
End Diff near zero suggests similar positioning at the current stage.
█ Settings
Period — groups data into Monthly, Quarterly, or Yearly periods.
Completed Periods to Compare — number of finished historical periods used in the comparison engine.
Chart Resolution — number of normalized steps used to draw each path.
-----------------
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.
Indicator
Regime - Market IntelligenceKnow if it's a bull market, bear market, or chop -- before you trade.
Regime classifies the market into BULL, BEAR, or CHOP using 6 weighted signals:
1. SMA 50/200 Crossover (25%)
2. Volatility Regime (15%) -- ATR expansion/compression
3. Volume Profile (15%)
4. RSI Momentum (15%)
5. MACD Trend (15%)
6. Fear/Greed Proxy (15%)
Features: color-coded background overlay, regime transition markers, signal breakdown table, confidence scoring, customizable weights, built-in alerts.
On-chart version of the Regime API (getregime.com). Full API adds real Fear and Greed, cross-exchange funding rates, macro overlay, crowd positioning, and liquidation data.
65% directional accuracy on 4h windows. 2700+ snapshots analyzed.
Free API: getregime.com/quickstart Indicator
Regime-Adaptive kNN Breakouts + Kalman Predictor [TechnicalZen]Regime-Adaptive kNN Breakout Classifier + Kalman Price Predictor
Why This Indicator Exists
Most breakout indicators treat every compression pattern equally. In reality, a volatility contraction forming during a high-ADX trending environment with surging volume behaves very differently from the same pattern in a choppy, low-volume consolidation.
This indicator addresses that gap by combining three distinct analytical engines:
Multi-Period Compression Detection — Scans across multiple bar periods to find the tightest range relative to recent history, identifying genuine volatility contraction zones where expansion is statistically likely.
Regime-Adaptive kNN Classification — A machine learning gate that evaluates the market regime surrounding each compression zone using Kalman-filtered features. Only setups with sufficient similarity to historically successful breakouts are allowed through.
Kalman Price Predictor — A state-space estimator tracking price position and velocity, enabling forward projection with a widening uncertainty cone.
The result is an indicator that learns which market conditions produce successful breakouts and provides a probabilistic price forecast — not just pattern detection.
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HOW IT WORKS
1. Multi-Period Compression Detection
The engine evaluates bar ranges across 2 to 20 periods, computing each period's range (highest high minus lowest low) and comparing it against the minimum range observed within an adaptive lookback window. When the current range is tighter than any historical range in the window, a compression zone is identified. The smallest qualifying period is selected — representing the most extreme volatility contraction.
An optional Inside Bar filter adds a complementary signal when the current bar's range is entirely contained within the prior bar.
2. ADX-Adaptive Lookback Window
The comparison window dynamically adjusts based on trend strength:
High ADX (strong trend) — shorter lookback, more responsive to compression during momentum phases
Low ADX (ranging market) — longer lookback, requiring more extreme contraction before triggering
This prevents the indicator from being too sensitive in trending markets or too sluggish in ranging conditions.
3. Kalman-Filtered Feature Space
Four market regime features are computed on every bar and smoothed through independent Kalman filters using a position + velocity state-space model. The Kalman filter reduces noise while tracking each feature's rate of change — achieving smoothing without the lag penalty of traditional moving averages.
The kNN classifier operates entirely on these Kalman-filtered features:
Relative Volume — Volume / SMA(Volume, 100) — captures participation surge or drought, Kalman-smoothed to filter out single-bar volume spikes
Relative ATR — ATR(14) / SMA(ATR, 100) — captures volatility expansion vs contraction regime, Kalman-smoothed for stable regime identification
ADX Normalized — ADX / 50 — measures trend strength (direction-agnostic), Kalman-smoothed to track trend momentum
Distance from MA — (Close - Trend MA) / ATR — price position relative to trend, Kalman-smoothed to reduce whipsaw noise
By filtering the feature space through the Kalman estimator before classification, the kNN operates on cleaner, denoised regime signals rather than raw noisy measurements. This is the critical link between the Kalman filter and the kNN — the classifier's accuracy depends on the quality of its input features.
4. kNN Breakout Classification
When a compression zone triggers a breakout, the classifier:
Constructs a feature vector from the four Kalman-filtered regime features
Scans the history buffer using Manhattan distance to find similar past regime conditions
Selects the k-nearest resolved neighbors — only TP (take-profit) and SL (stop-loss) outcomes vote; pending and time exits are excluded entirely
Computes a distance-weighted classification score where closer neighbors have proportionally more influence
Compares the score against the user-defined confidence threshold
If the score falls below the threshold, the setup is silently skipped. The classifier has learned which combinations of volume regime, volatility regime, trend strength, and price position tend to produce winning breakouts.
Key design choices:
Adaptive k — k = floor(sqrt(resolved outcomes)), clamped between user-defined min/max. The number of neighbors consulted grows naturally as the classifier accumulates experience, preventing overfitting to sparse early data.
Warmup phase — During the first N resolved outcomes, all setups pass through to build the training set. The classifier only begins filtering after accumulating sufficient data.
Feedback loop — Every exit writes its outcome back to the history buffer. TP exits score 1.0, SL exits score 0.0. The classifier genuinely learns from the specific chart and timeframe it is applied to.
Distance-weighted voting — Prevents outlier neighbors from distorting the classification. A very close TP neighbor outweighs several distant SL neighbors, producing more nuanced probability estimates.
5. Kalman Price Predictor
A fifth Kalman filter runs on price itself, maintaining three estimates simultaneously:
Filtered position — optimal smoothed price estimate
Velocity — estimated rate of price change per bar
Covariance matrix — estimation uncertainty and cross-correlations
The velocity component enables forward projection: Predicted Price = Filtered Position + Velocity x Projection Bars . The uncertainty cone is scaled by ATR and widens proportionally to the square root of the projection horizon — reflecting the theoretical uncertainty growth of price over time.
Projection trail: The last 5 projections are displayed with graduated transparency (50% to 90%), creating a visual history of how the forecast has evolved. A consistent, parallel trail suggests strong directional conviction; a diverging or oscillating trail signals uncertainty.
6. Trend-Aware Exit System
The exit system uses four complementary mechanisms, each feeding outcomes back to the kNN:
Take Profit — R-multiple target (default 2R, where R = compression zone range). Scored as 1.0 in kNN feedback.
Stop Loss — Opposite side of compression zone, optionally requiring price to also be wrong-side of the Trend MA. This trend-aware condition reduces whipsaw stops in strong trends. Scored as 0.0 in kNN feedback.
Trailing Stop — Activates after 1R profit, trails by ATR x multiplier. Dynamic protection that locks in gains.
Time Exit — Maximum bars in trade before forced exit. Scored as 0.5 (neutral) — neither rewarding nor penalizing the kNN for inconclusive setups.
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VISUAL GUIDE
Chart Elements
Compression boxes — Colored zones marking detected volatility contraction (green = bullish breakout, red = bearish)
Extended levels — Dotted lines projecting the high and low of each compression zone forward
Entry labels — Direction and kNN confidence percentage (e.g., "Long 72.5%")
Exit labels — TP / SL / T markers with R-multiple detail in tooltip
Projection line — Dashed line extending forward from Kalman-filtered price
Uncertainty cone — ATR-scaled filled area widening into the future
Projection trail — 5 fading historical projections showing forecast evolution
Kalman price line — Optional smoothed price curve (off by default)
Dashboard (bottom-right)
Win Rate — Percentage of resolved trades hitting TP (tinted green or red)
Trades — Win / Loss count
Mode — Distance-weighted classification
Phase — Warmup (building data) or Active (filtering enabled)
k — Current adaptive k value
Score — Latest kNN confidence score
History — Buffer fill level (e.g., 45/60)
Projection — Predicted price with directional arrow
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SETTINGS GUIDE
Detection
Enable Inside Bar (default: On) — Include Inside Bar patterns alongside compression detection
Adaptive kNN
Enable kNN Filter (default: On) — Toggle the ML classification gate
k Min / k Max (default: 2 / 10) — Bounds for adaptive k. Auto-scales with sqrt of resolved outcomes
Confidence Threshold (default: 0.25) — Minimum kNN score to accept a setup. Lower values are more permissive; higher values are more selective
Min Resolved to Activate (default: 15) — TP/SL outcomes needed before the classifier begins filtering
History Buffer Size (default: 60) — Maximum stored breakout patterns for comparison
Kalman Filter
Process Noise Q (default: 0.01) — Controls how much the filter expects the underlying signal to change between bars. Higher values make the filter more responsive but noisier
Measurement Noise R (default: 0.10) — Controls how much the filter distrusts each new measurement. Higher values produce smoother output with more lag
Show Price Projection (default: On) — Display the forward projection line and uncertainty cone
Projection Bars (default: 10) — How far forward to project price
Projection Color (default: Aqua) — Color for all projection elements
Show Uncertainty Cone (default: On) — Display the ATR-scaled confidence band
Cone Width (default: 1.0 ATR) — Width multiplier for the uncertainty cone. Adjustable per instrument
Show Kalman Price Line (default: Off) — Display the smoothed Kalman price estimate on chart
Trend Filter
Enable Trend Filter (default: On) — Restrict breakouts to trend-aligned direction only
Trend MA Mode (default: Adaptive) — Static = fixed MA length; Adaptive = MA length scales dynamically with the compression lookback
MA Type (default: EMA) — Exponential or Wilder's (RMA) moving average
Adaptive Multiplier (default: 2.0) — Lookback x Multiplier = MA length in adaptive mode
Static MA Length (default: 200) — Fixed MA length when in static mode
Adaptive Look Back
Look Back Mode (default: ADX Adaptive) — Static = fixed comparison window; ADX Adaptive = window scales with trend strength
ADX Length (default: 14) — Period for ADX calculation
ADX Low / High (default: 10 / 35) — ADX range mapped to lookback bounds. Higher ADX compresses the lookback
LB Min / LB Max (default: 20 / 120) — Minimum and maximum lookback window size
Exits
TP (R-multiple target) (default: On) — Take-profit at R-multiple of compression zone range
SL (opposite side) (default: On) — Stop-loss at opposite boundary of compression zone
Target R (default: 2.0) — Take-profit distance as multiple of range
Trend-Aware SL (default: On) — SL only triggers when price is also wrong-side of Trend MA
Trailing Stop (default: On) — Trails by ATR x multiplier after 1R profit
Trail ATR Multiplier (default: 1.5) — Trail distance = ATR(14) x this value
Time Exit (default: On, 50 bars) — Force exit after maximum bars in trade
Visual Settings
Bull / Bear / Time colors — Customizable directional colors
Box Fill / Border Transparency — Compression zone box appearance
Extend Levels (default: 50 bars) — Forward projection distance for compression zone levels
Level Width / Style — Line appearance for projected levels
Max Patterns Kept (default: 120) — Maximum drawing objects maintained on chart
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THE KALMAN-kNN PIPELINE
The two ML components are not independent — they form a pipeline:
Kalman filters denoise the four regime features on every bar, producing clean estimates of volume regime, volatility regime, trend strength, and price position
kNN classifier operates on these Kalman-filtered features, comparing the current denoised regime against historically successful and unsuccessful breakout conditions
Kalman price filter independently tracks price dynamics, projecting the estimated trajectory forward with quantified uncertainty
The classifier's accuracy fundamentally depends on the quality of its input features. By feeding Kalman-filtered signals rather than raw measurements, the kNN compares regime states rather than noisy observations — producing more stable and meaningful similarity assessments.
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CREDITS AND ACKNOWLEDGMENTS
This indicator builds upon concepts from two published works:
Smart NR2–NR20 and Inside Bar by Zeiierman — multi-period compression detection, adaptive lookback via ADX, and breakout trigger architecture
kNN Market Architecture by LuxAlgo — application of k-nearest neighbors classification to filter market signals using relative volatility and volume features
Original contributions in this indicator:
Kalman filter state-space estimation for feature smoothing (position + velocity model with full covariance tracking)
Kalman-to-kNN pipeline — classifier operates on denoised regime features, not raw measurements
Regime-adaptive kNN classification with distance-weighted voting on resolved outcomes only
Real-time feedback loop where exit outcomes update the kNN training data
Adaptive k scaling based on accumulated classifier experience
Kalman price predictor with forward projection and ATR-scaled uncertainty cone
Graduated projection trail showing forecast evolution
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This indicator is for educational and informational purposes only. It does not constitute financial advice. All investments involve risk, and past performance does not guarantee future results. The kNN classifier learns from historical patterns on the specific chart and timeframe it is applied to — its effectiveness may vary across different instruments and market conditions. Always conduct your own analysis and risk management.
Indicator
Esco Psychological Theory [v1]Esco Psychological Theory
An experimental framework for visualizing market psychology, crowd positioning, and institutional intent — derived entirely from price structure.
-Experimental Indicator
This tool does not generate buy or sell signals.
Esco Psychological Theory is a psychological lens — a way of interpreting what participants are likely feeling and who benefits from those emotional conditions.
Treat it as a research framework, not a trading system.
What This Is
Price does not simply move between support and resistance.
It moves through emotional states.
Every candle on your chart represents thousands of decisions made under fear, greed, hope, regret, and panic. Those emotions are not random — they tend to appear in recognizable structural patterns.
Smart money does not simply buy low and sell high.
It often creates the emotional conditions that force the crowd to do the opposite.
Esco Psychological Theory attempts to model this process. It reads structure, volatility expansion, displacement, liquidity sweeps, failed breakouts, and wick behavior — then infers what market participants are likely experiencing and how institutional players may be responding.
This indicator is not trying to predict price.
It is trying to frame why price may be behaving the way it is.
The Psychological Model
Markets tend to cycle through recognizable emotional regimes.
This indicator models those transitions using a sequential state machine. Regimes progress through adjacent states rather than jumping randomly, producing a more realistic psychological narrative.
The cycle:
COMFORT → TENSION → HOPE → TRAP RISK → PANIC → CAPITULATION → RELIEF → REACCUMULATION → …
Each regime leaves structural fingerprints that can be observed in price behavior.
Comfort
Low volatility, orderly trend behavior, shallow pullbacks.
The crowd feels positioned and confident.
This is often where smart money quietly builds exposure.
Tension
Equal highs/lows begin forming.
Repeated rejection at key levels.
Volatility compresses.
Something is building.
Hope
A displacement candle breaks structure.
Breakout traders enter aggressively.
Momentum appears convincing.
The move looks real.
Trap Risk
The breakout stalls or fails to continue.
Price reclaims prior levels.
Large wicks appear at extremes.
Late entries are now vulnerable.
Panic
Structure shifts against the prior trend.
Stops trigger.
Positions unwind quickly.
Volume spikes.
Capitulation
Consecutive displacement candles appear.
Multiple structure breaks occur rapidly.
Maximum forced repositioning.
Relief
Volatility begins to decline.
Price stabilizes and the market pauses.
Participants exit remaining positions.
Reaccumulation
Compression forms around new price levels.
Fresh pivots emerge.
Smart money quietly finishes positioning for the next cycle.
Modules
Emotional Regime Engine
Classifies the market’s current psychological regime using the sequential state model.
Transitions are constrained to realistic sequences rather than random jumps.
Labels appear only when the regime changes.
Optional background shading and a timeline ribbon allow you to visually track emotional phases across the chart.
Smart Money Intent
Estimates institutional behavior based on structural evidence.
Six possible classifications are evaluated simultaneously with confidence scoring.
Accumulation
Repeated demand absorption and compression near discount levels.
Distribution
Repeated supply rejection and compression near premium levels.
Liquidity Harvest
Sweeps of equal highs or lows followed by sharp displacement reversals.
Trap Engineering
Failed breakouts combined with equal level buildup and overextension.
Passive Absorption
Quiet wick rejection and declining volume at key levels.
Aggressive Repricing
Consecutive displacement candles and decisive structure breaks.
Crowd Bias
Infers likely crowd positioning based on structure alignment and momentum behavior.
Possible states include:
Positioned Long / Positioned Short
Trapped Long / Trapped Short
Chasing Momentum
Indecisive / Neutral
Pain & Pressure Engine
Estimates where future price movement would create the greatest psychological stress.
Pain direction is derived from:
trapped positioning
recent liquidity sweeps
failed breakout attempts
distance from equilibrium
premium / discount positioning
Pressure intensity (0–100%) measures the amount of latent repositioning energy in the market.
When pressure exceeds 70%, candles receive a subtle amber tint.
Soft gradient bands above and below price indicate potential pain direction — areas where movement could force the most participants to react.
Psychological Pressure Zones
Event-driven zones are created when structural events occur.
FOMO Zones
Breakout areas where late buyers or sellers entered.
Regret Zones
Failed breakout ranges containing trapped traders.
Trap Zones
Sweep-and-reclaim areas where liquidity was harvested.
Forced Zones
Panic and capitulation ranges created during liquidation events.
Zones automatically deduplicate, fade with time, and disappear once price cleanly resolves through them.
Premium / Discount Context
Using the most recent major swing high and low, the indicator calculates range positioning.
The chart displays:
Premium (top 25%)
Discount (bottom 25%)
Equilibrium midpoint
The dashboard shows the exact percentage location within the range.
Dashboard
A compact panel summarizes the full psychological read of the market.
Displayed metrics include:
Regime — current emotional state
Crowd — inferred crowd positioning
Intent — smart money classification with confidence score
Pain — directional pain bias
Pressure — psychological pressure intensity
Zone — premium / discount / equilibrium position
Phase — cycle phase progression
What This Indicator Is Not
This indicator does not predict price direction.
It does not have access to order flow, liquidation data, or actual market positioning.
Instead, it infers probable psychological conditions from the structural footprint that emotion leaves on a chart.
The classifications and intent scores are probabilistic interpretations, not definitive signals.
Use this as one analytical layer alongside your own discretionary framework.
Inputs
All modules can be enabled or disabled independently.
Key configuration options include:
Swing Lookback
Major Swing Lookback
Maximum Zone Age / Visible Zones
Regime Background and Timeline Ribbon
Pain Gradient and Pressure Bar Colors
Premium / Discount Shading
Event Markers (displacement candles, sweeps, MSS, squeeze events)
Notes
Overlay indicator (drawn directly on the price chart)
Pine Script v6
Compatible with all markets and timeframes
Lower timeframes may require smaller swing lookback values (10–14 recommended)
Higher timeframes benefit from larger values (21–50 recommended)
Feedback
This is the first public release of Esco Psychological Theory.
The framework is experimental and will continue evolving.
If you test it and have feedback, ideas, or suggestions for improving the psychological model or visual design, I would genuinely love to hear them.
Community input is welcome and appreciated.
Esco Psychological Theory
Structure reveals emotion.
Emotion reveals intent. Indicator
Trend Zone Dashboard with Auto S/R [PhenLabs]Trend Zone Dashboard with Auto Support/Resistance
Version: PineScript™ v6
📌 Description
The Trend Zone Dashboard with Auto Support/Resistance is a professional-grade, self-calibrating support and resistance detection system. It automatically scans for pivot highs and lows across a configurable lookback window, clusters them into consolidated price zones using an adaptive tolerance algorithm, then scores each zone by touch frequency and bounce rate. The result is a clean set of actionable S/R zones rendered directly on the chart with an accompanying data-rich dashboard — no manual level-drawing required.
🚀 Points of Innovation
Auto Mode with Binary Search Calibration: A built-in iterative algorithm automatically tunes clustering tolerance to converge on a user-defined target number of zones (default: 5), eliminating the need for manual parameter tweaking across different instruments and timeframes.
Statistical Zone Scoring: Each zone is scored by both touch count (how often price interacts with the zone) and bounce rate (percentage of touches that produced confirmed reversals), giving traders a quantified measure of zone reliability.
Greedy Merge Clustering: Sorted pivot prices are merged using an ATR-adaptive or percentage-based tolerance, producing naturally consolidated zones that reflect true areas of price memory rather than arbitrary horizontal lines.
🔧 Core Components
Pivot Detection Engine: Uses `ta.pivothigh()` and `ta.pivotlow()` with configurable strength to identify swing points. Raw pivots are accumulated incrementally across all bars for efficiency, then filtered to the lookback window on the final bar.
Adaptive Clustering Algorithm: In Auto Mode, a 15-iteration binary search explores tolerance values between 0.1× ATR and 8× ATR, counting the resulting clusters at each step until the output converges to ±1 of the target zone count. In Manual Mode, the user directly sets ATR multiplier or percentage threshold.
Touch & Bounce Tracker: On the last bar, the engine scans the full lookback window bar-by-bar for each zone. A “touch” occurs when a bar’s high-low range overlaps the zone boundary. A “bounce” is confirmed when the close moves away from the zone midpoint relative to the prior close, distinguishing genuine rejections from breakdowns.
Directional Pruning System: Zones are intelligently removed only when price has decisively broken through them in the correct direction — support zones are pruned only if price collapses far below them, and resistance zones only if price surges far above. This prevents valid zones from being erroneously discarded.
🔥 Key Features
Dynamic Dashboard Table: An on-chart table (positionable to any corner) displays each active zone’s price level, type (Support/Resistance), pivot confluence count, touch strength, distance from current price, and bounce rate — all color-coded for instant readability.
Strength-Scaled Zone Boxes: Zones are drawn as shaded rectangular regions on the chart, with transparency inversely proportional to their strength score. Stronger zones appear more vivid; weaker zones fade into the background.
Color-Coded Bounce Rate: High bounce rates on support zones glow green; high bounce rates on resistance zones glow red. Low-confidence zones are dimmed to gray, directing attention to the most actionable levels.
Pivot Confluence Column: Shows how many raw pivot points were merged into each cluster, providing a confluence metric independent of the touch count.
Info Footer Row: The dashboard footer displays the current mode (Auto/Manual), computed tolerance, total pivot count, and lookback depth for full transparency into the algorithm’s behavior.
🎨 Visualization
Zone Boxes: Support zones rendered in green, resistance zones in red, extending from the lookback origin to 25 bars into the future. Width reflects the natural spread of the clustered pivot prices.
Zone Labels: Compact labels at the right edge of each zone box display type, price level, touch count, and bounce rate at a glance.
Dashboard Table: A 6-column professional table with a blue header row, color-coded data cells, and a gray info footer. Fully repositionable via dropdown input.
📖 Usage Guidelines
Auto Mode (Recommended): Leave Auto Mode enabled with the default target of 5 zones. The algorithm will self-calibrate to produce approximately 5 meaningful S/R zones on any instrument or timeframe. Increase the target for more granular analysis or decrease it for a cleaner chart.
Lookback Period: The default of 200 bars works well for most scenarios. Increase to 500+ on higher timeframes (Daily, Weekly) to capture macro structure. Decrease to 50–100 on scalping timeframes for more responsive zones.
Pivot Strength: Controls the minimum swing significance. Higher values (8–15) produce fewer but more significant pivots. Lower values (2–4) capture minor swings and produce denser zone coverage.
Manual Mode: Disable Auto Mode to take direct control of clustering tolerance. Use ATR multiplier for volatility-adaptive clustering, or percentage threshold for fixed-width zones relative to price.
Breakout Pruning: The breakout ATR multiplier (default 2.0) controls how far price must close beyond a zone before it’s considered invalidated. Increase for more persistent zones; decrease for faster pruning.
✅ Best Use Cases
Key Level Identification: Automatically surface the most statistically significant support and resistance levels without manual drawing, ideal for traders who analyze multiple instruments.
Zone Quality Assessment: Use the bounce rate column to distinguish between zones that consistently produce reversals versus zones that price tends to slice through — critical for setting stop-loss and take-profit targets.
Confluence Trading: Zones with high pivot counts AND high touch counts represent areas where price has repeatedly found significance from multiple independent swing points, offering the highest-probability trade setups.
Breakout Validation: When a zone with a historically high bounce rate is finally broken (pruned from the dashboard), it signals a genuine structural shift rather than a false breakout.
Multi-Timeframe Analysis: Run the indicator on your execution timeframe with a long lookback to naturally capture higher-timeframe structure within a single instance.
⚙️ Settings Overview
Auto Mode (Default: On) — Enables intelligent self-calibration of clustering parameters.
Target Number of Zones (Default: 5) — The desired number of S/R zones in Auto Mode. Range: 2–15.
Lookback Period (Default: 200) — Number of bars to scan for pivots. Range: 20–1000.
Pivot Strength (Default: 5) — Left/right bar count for pivot confirmation. Range: 2–20.
Clustering Method (Default: ATR) — ATR-based or Percentage-based tolerance for manual mode.
ATR Multiplier (Default: 1.0) — Multiplier applied to ATR for zone merge tolerance in manual mode.
Percentage Threshold (Default: 0.5%) — Fixed percentage tolerance for zone merging in manual mode.
Minimum Touches (Default: 2) — Zones with fewer touches are filtered out (manual mode only; auto mode uses 1).
Maximum Zones (Default: 8) — Hard cap on displayed zones.
Breakout Pruning (Default: 2.0× ATR) — Distance beyond zone edge required to consider it broken.
Dashboard Position (Default: Top Right) — Corner placement for the dashboard table.
Show Zone Boxes (Default: On) — Toggle chart zone rendering.
Show Zone Labels (Default: On) — Toggle zone annotation labels.
Support/Resistance Colors — Fully customizable zone and dashboard color scheme.
💡 Note
This indicator performs its full computation on the last bar only (`barstate.islast`), making it lightweight regardless of chart history length. The Auto Mode binary search converges in ≤15 iterations, adding negligible overhead. For best results, ensure your chart has sufficient history loaded (at least 200+ bars) so the pivot detection engine has adequate data to identify meaningful swing points. Always use this tool in conjunction with price action context and broader market structure analysis.
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Opening Range BoxOpening Range Box
Opening Range Box highlights the high and low of a user-defined opening session and visualizes the range directly on the chart. The script tracks price during the selected session window and dynamically builds a range using the highest high and lowest low that occur within that period. As the session progresses, the range updates in real time so traders can see the developing structure of the opening market activity.
Once the session begins, the indicator starts calculating the opening range and draws a box around the price action between the session high and low. At the same time, horizontal lines are plotted at the high and low levels of the range. These levels represent important reference points that many intraday traders use to identify potential breakout, breakdown, or support and resistance zones.
After the opening session ends, the final range is locked in. If enabled, the high and low levels can automatically extend to the right side of the chart so they remain visible for the rest of the trading session. This allows traders to easily monitor how price interacts with the opening range throughout the day.
An optional midpoint line can also be displayed. This dashed line represents the 50% level of the opening range and can be used as an additional reference level for balance, mean reversion, or intraday bias.
All visual elements can be customized. Users can control the session time, enable or disable the range box, show or hide the midpoint, extend the range levels across the chart, and adjust colors and line width to match their chart layout.
The default session is set to 09:30–10:00 to match the first thirty minutes of the U.S. equities market open, but it can be changed to any time window to suit different markets or trading strategies. The indicator is designed for intraday charts and is commonly used for opening range breakout strategies and early-session support and resistance analysis. Indicator
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