Navigator Volume Profil FixedLong Term Investing
Day Trading
Navigator Volume Profile Fixed (Fixed + Current Session)
**Navigator Volume Profile Fixed** plots a horizontal volume profile on your chart using a **fixed timeframe anchor** (ex: Daily) and optionally overlays a **live “current” profile** for the active session/period.
It’s designed to help you quickly see where volume is building (acceptance) vs. thinning out (rejection), and to identify the key reference levels traders watch most: **PoC, VAH, and VAL**.
### What it plots
**Fixed Volume Profile (anchored to a timeframe)**
Builds a completed profile each time the selected anchor timeframe rolls over (ex: each new day on a Daily anchor).
**Current Volume Profile (live)**
Continuously updates the developing profile for the current anchor period (optional toggle).
**Point of Control (PoC)**
Highlights the single price level with the highest traded volume.
**Value Area (VAH / VAL)**
Plots the Value Area boundaries using a configurable percentage (default **68%**), and visually differentiates the value area from the rest of the profile.
Key settings
* **Enable Fixed VP**: turn the fixed/anchored profile on/off
* **Timeframe Anchor**: choose the profile reset period (ex: 1D)
* **Show Current Fixed VP**: show/hide the developing (current) profile
* **Number of Rows**: controls profile resolution (price “bins”)
* **Profile Width (%)** and **Bar Thickness**: visual scaling controls
* **PoC + Value Area toggles**: show/hide PoC and VA boundaries
* **Extend PoC Line**: optionally extend the PoC into the future
How to use it (practical)
* Treat **PoC** as the most accepted price for the anchored period.
* Use **VAH/VAL** as reference boundaries for balance vs. imbalance.
* Compare **Fixed** vs **Current** profiles to see whether volume is migrating higher/lower during the session and where price is building acceptance.
**Note:** This script draws using TradingView line objects and is optimized to stay within platform limits while maintaining a clean profile display.
Search in scripts for "imbalance"
KIMATIX FVG/IFVG/BPRProfessional Fair Value Gap & Imbalance Toolkit
The KIMATIX FVG/IFVG/BPR indicator is a precision tool designed to identify institutional inefficiencies in price:
Fair Value Gaps (FVG), Inverse Fair Value Gaps (IFVG) and Balanced Price Ranges (BPR) — clean, minimal and non-repainting.
This indicator is built for scalpers, intraday traders and smart-money traders who want to trade where price is most likely to react, not where indicators lag.
What this indicator shows
Fair Value Gaps (FVG)
Detects bullish and bearish FVGs using strict 3-candle imbalance logic
Highlights areas where price moved too fast, leaving inefficient structure
Ideal for:
Continuation trades
Pullback entries
Reaction zones after impulse moves
Color-coded
🟢 Bullish FVG
🔴 Bearish FVG
Inverse Fair Value Gaps (IFVG)
Automatically detects when an FVG is invalidated
Marks the same zone as an Inverse FVG
Extremely useful for:
Failed structure setups
Reversal trades
Stop-hunt & liquidity traps
Color-coded
🟡 IFVG (invalidation zone)
Balanced Price Range (BPR)
Detects overlapping bullish & bearish FVGs
Highlights price areas where buying and selling pressure are balanced
These zones often act as:
High-probability reaction areas
Compression zones before expansion
Premium intraday decision levels
Color-coded
🔵 BPR (balanced price range)
Smart, Clean & Non-Repainting
Non-repainting
Only the last 3 active zones are shown → no clutter
Boxes extend forward with a manual cap (user-controlled)
Designed for 1m – 15m execution, works on all markets
Futures, Crypto, FX, Indices, Stocks
How professionals use it
Combine FVGs with:
VWAP
Session highs/lows
Volume Profile (POC / VAH / VAL)
Market structure (BOS / displacement)
Use IFVGs to spot failed smart-money narratives
Use BPRs as decision zones, not blind entries
This indicator does not give buy/sell signals.
It shows you where trades make sense — execution is up to you.
Best use cases
Scalping (1m–3m)
Intraday trading (5m–15m)
Smart-money concepts
Liquidity-based trading
News reactions & stop runs
Learn how to trade it properly
This indicator is part of the KIMATIX Trading Framework.
More education, live examples & full system:
kimatixtrading.com
LHAMA MTF Structure & Fibs [LTS]Overview
LHAMA MTF Structure & Fibs is a multi-purpose market structure toolkit that combines current-timeframe structure, higher-timeframe structure, Imbalance/FVG-based order blocks, and automatic Fibonacci retracements into a single chart overlay.
Current-Timeframe Structure
The indicator first maps current-timeframe market structure using swing highs and lows based on a user-defined pivot length (“Time-Horizon”):
Labels swing points as HH , HL , LH , and LL .
Draws BOS (Break of Structure) when price breaks beyond a prior swing.
Optionally identifies CHoCH (Change of Character) when a break occurs against the previous direction.
Lets you choose whether BOS/CHoCH confirmation uses closes or wicks .
Provides options to show/hide swing labels, choose line style (solid/dashed/dotted), and configure bullish/bearish colors.
Higher-Timeframe (HTF) Structure
On top of the local structure, the script builds a higher-timeframe structure map and projects it onto your active chart:
Aggregates price into HTF “bars” (e.g., 4h structure on a 5m chart).
Detects HTF pivots with their own pivot length setting.
Draws HTF BOS/CHoCH lines and labels back on the lower timeframe.
Lets you choose wick vs close confirmation for HTF breaks.
Optional “ pending ” HTF levels: lines extended from the latest HTF swing highs/lows that remain “waiting” until price breaks them.
This is designed to make it easier to see how intraday price is moving relative to the dominant higher-timeframe trend.
Order Blocks (Imbalance/FVG-Based)
The indicator detects simple bullish and bearish order blocks based on fair value gaps and prior sweeps:
Identifies bullish/bearish FVGs together with a sweep of a previous low/high.
Creates colored boxes anchored to an “anchor” candle and extends them forward.
Marks boxes as “broken” when price trades inside or through the opposite side.
Broken blocks can have reduced emphasis (more transparent, dashed border) and can optionally be deleted.
Show Nearest Only mode highlights only the closest active bullish and bearish blocks to reduce chart clutter.
Periodic cleanup removes very old boxes to maintain chart responsiveness.
Automatic Fibonacci Levels
The script can draw up to five customizable Fibonacci retracement levels using the HTF structure logic:
Measures swings using HTF pivots and extremes.
Historical mode : measures between two confirmed pivots in one direction.
Live mode : starts from the last confirmed pivot and tracks the evolving extreme; if price reverses through that pivot, measurement can flip to track the new leg.
Each Fib level has its own on/off toggle, ratio value, and color.
Draws a main swing line plus retracement lines projected slightly into the future.
Key Inputs & Customization
Market Structure (Current TF)
Pivot length (“Time-Horizon”).
BOS confirmation: candle close or wicks.
BOS/CHoCH line style and width.
Swing labels on/off and global label size.
Bullish/bearish colors.
Market Structure (HTF)
HTF timeframe selection.
Separate pivot length for HTF swings.
Close vs wick confirmation for HTF breaks.
HTF swing labels and CHoCH labels on/off.
Pending HTF levels: style, color, and visibility.
Order Block Settings
Bullish/bearish box colors and border width.
Maximum number of boxes to display.
Optional deletion of broken blocks.
“Show Nearest Only” filter to highlight the closest active zones.
Max bars to backscan for the anchor candle.
Cleanup frequency for removing very old boxes.
Fibonacci Settings
Show/hide auto Fibs.
Historical vs Live tracking mode.
Five user-defined ratios with individual toggles and colors.
Trading Playbook Panel (SMC + EW + Sniper)🔥 What This Script Does
The indicator creates a visual floating panel containing:
1. HTF Bias Framework (H4 → H1 → M15)
Guides you through determining trend, liquidity direction, imbalance zones, and institutional order flow.
2. Valid Setup Models
Covers both:
Continuation setups (displacement → OTE → FVG entry)
Reversal setups (liquidity sweep → CHoCH → retest)
3. 5-Minute Sniper Entry Checklist
Ensures high-precision entries with:
Liquidity sweep
CHoCH
Displacement
FVG formation
Retest entry
Strict invalidation rules
This is the exact logic used in prop-firm and institutional trading models.
4. Stop-Loss & Invalidation Rules
Built with institutional logic:
SL beyond liquidity sweep
SL beyond invalidation swing
Works for both BUY and SELL setups.
5. Multi-Stage Take Profit Mapping
Including:
Internal liquidity
Equal highs/lows
Imbalance
Opposite OB
HTF draw
Designed for partials + runners.
6. Risk-Management System
A complete discipline structure:
0.5–2% risk per setup
Max daily loss
Max trades per day
Stop-after-loss rule
No chasing / no mid-range entries
7. Pre-Trade Checklist
A professional assessment framework to verify trade quality.
8. Trading Psychology Principles
Reinforces mindset, discipline, and patience.
⭐ Who This Script Is For
This tool is ideal for:
SMC traders
ICT style traders
Elliott Wave traders
Scalpers & intraday traders
Prop-firm challengers
Anyone wanting to follow a repeatable, rules-based system
It keeps you consistent, structured, and focused on the highest-probability setups.
🧠 Why This Script Works
Most traders lose because they:
Enter impulsively
Skip rules
Don’t analyze multi-timeframe structure
Enter without liquidity confirmation
Use random entry zones
This script eliminates that.
It forces a clear, step-by-step process:
1️⃣ Top-down bias
2️⃣ Liquidity location
3️⃣ Sweep → CHoCH → Displacement
4️⃣ Refined 5M entry
5️⃣ Strict SL & TP rules
It removes emotion and replaces it with pure process.
⚙️ Customizable
Move the panel anywhere on the chart
Change panel colors
Change text colors
Perfect for dark or light mode
🎯 Summary
This is not a trading signal indicator.
This is your rulebook, your discipline engine, and your playbook — right on your chart.
It keeps you aligned with the highest-probability setups used by advanced SMC and EW traders.
Use it before every trade.
Trade like a professional — every day.
BEGGALKey Features and Concepts
1. Order Block (OB) Identification (Pivots)
The core of the indicator relies on Pivot Point detection (ta.pivothigh/ta.pivotlow) over a specified Pivot Length (e.g., 5 bars).
Bullish OB (Demand Zone): Identified at a valid low pivot point, with the zone boundary defined between the pivot low (low ) and the open/close average (hl2 ) of the pivot bar.
Bearish OB (Supply Zone): Identified at a valid high pivot point, with the zone boundary defined between the pivot high (high ) and the open/close average (hl2 ) of the pivot bar.
2. Advanced Strength Filters (Momentum & Volume)
The indicator applies strict filters to ensure only powerful, high-quality zones are drawn:
Momentum (ATR) Filter: Checks if the candle that created the OB has a range (high - low) greater than the Average True Range (ATR) multiplied by the Momentum Threshold. This filters for impulsive, strong candles.
Volume Imbalance Filter (SMC Confirmation): If enabled, it requires the volume of the OB-creating candle to be higher than the volume of candles surrounding it (checked over the Volume Imbalance Lookback period). This confirms institutional activity in the zone creation.
Structure Break Filter (BOS/CHoCH): If enabled, the OB is only considered valid if it is created after a Break of Structure (BOS) or Change of Character (CHoCH). This validates the zone according to market structure rules (e.g., a Bearish OB must be preceded by a break of a significant swing low).
3. Dynamic Zone Management
Zone Narrowing (enable_narrowing): This feature dynamically adjusts the boundaries of an Order Block after it has been touched. If a candle wick tests the zone without fully mitigating it, the zone boundary is moved inward to the point where the test occurred, narrowing the zone and making it a more precise entry point (Dynamic OB concept).
Mitigation/Removal: Once price action (either the candle's wick or close, based on the Mitigation Method setting) breaches the outermost boundary of the zone, the Order Block is considered mitigated (broken) and is removed from the chart to clear clutter.
4. Risk Categorization
The indicator tracks and draws up to a user-defined number of OBs (Bullish/Bearish OB Count). These are categorized by their index:
Index 0 (Closest): Categorized as High Risk Zone.
Index 1: Categorized as Medium Risk Zone.
Index 2 and beyond: Categorized as Low Risk Zone. The user can toggle the visibility for each of these risk categories.
5. Integrated Risk/Reward (RR) Setup
For the High Risk Zone (Index 0), once the zone is touched, the indicator displays a complete trade setup:
Entry: Assumed at the Average Price of the Order Block.
Stop Loss (SL): Placed at the protective boundary of the OB (the top for a Sell Zone, the bottom for a Buy Zone). The risk area is colored with the RR Risk Zone Background.
Take Profit (TP): Calculated based on the user-defined Risk/Reward Ratio (e.g., 2.0 for 1:2 RR). The reward area is colored with the RR Reward Zone Background.
The RR boxes and price labels (TP/SL) are drawn with a configurable RR Box Width (Bars).
6. Alerts
The indicator includes built-in Pine Script alerts that trigger when the price enters an unmitigated zone, notifying the user of the Risk Level (High, Medium, or Low), the zone's boundaries, and the price.
RSI Volume Order BlocksOverview
This script builds structured order blocks using a combination of RSI pivots, price structure, and optional volume/ATR-based scaling.
It is designed to create a clean, explainable map of support/resistance levels that respond only to meaningful momentum shifts rather than small, insignificant oscillations.
Core Idea
Traditional order blocks rely solely on price highs/lows, which often produces excessive or noisy zones.
This model instead:
Detects pivot highs/lows on the RSI (controlled by RSI Length and Sensitivity).
Generates bearish order blocks from RSI pivot highs and bullish order blocks from RSI pivot lows.
Allows the user to choose whether blocks are based on candle bodies or the full candle range.
Optionally filters blocks so that:
bearish OBs form only when RSI is above an overbought threshold,
bullish OBs form only when RSI is below an oversold threshold.
The resulting zones represent areas of momentum exhaustion and imbalance rather than random price fluctuations.
Volume–ATR Height Mode
The script offers two approaches for block height:
1. Price Candle Mode
Block height equals either:
the candle body, or
the full high–low range of the pivot bar.
2. Volume–ATR Mode
Block height is adaptively scaled using:
ATR (ATR Length for Height),
relative volume compared to a baseline (Volume Baseline Length),
a global height multiplier.
This makes zones thicker when the pivot candle had both higher volatility and above-average volume, and thinner when market participation was lower.
Lifespan and Mitigation
Each block extends forward in time until price mitigates it.
Mitigation Method: Close
Bearish OB is removed when a candle closes above its top.
Bullish OB is removed when a candle closes below its bottom.
Mitigation Method: Wick
Bearish OB is removed when a wick breaks above the top.
Bullish OB is removed when a wick breaks below the bottom.
Additional controls:
Maximum number of stored OBs per side.
Maximum number of displayed OBs per side.
Overlap filtering to avoid redundant zone stacking.
Main Inputs (Summary)
RSI Length – standard RSI lookback.
RSI OB Sensitivity – pivot aggressiveness (higher = fewer, stronger pivots).
Overbought/Oversold Levels – thresholds for optional filters.
RSI Filter –
bearish OB only if RSI > overbought,
bullish OB only if RSI < oversold.
Order Block Style – candle body or full range.
Mitigation Method – close-based or wick-based.
OB Height Mode – price candle or volume–ATR scaling.
Volume Baseline Length, ATR Length for Height, Height Scale – parameters for adaptive height mode.
Show Bullish / Bearish OBs – toggles for each side.
Color settings for zone visualization.
How to Use
Typical workflows include:
Using higher-timeframe OB zones as structural support/resistance, then refining entries on lower timeframes.
Watching for price reactions inside thick Volume–ATR zones, which may indicate areas of strong participation.
Combining this tool with trend filters, volume metrics, or price action confirmation (e.g., rejection wicks or engulfing patterns).
This script does not generate automated entries/exits; it is a contextual mapping tool designed to highlight where meaningful imbalance likely originated and where reactions may occur.
Notes
Works on any symbol and timeframe available on TradingView.
Most effective when combined with disciplined risk management and a defined trading plan.
Provided for research, chart analysis, and backtesting.
Disclaimer
This tool is for educational and informational purposes only.
It does not constitute financial advice or a recommendation to buy or sell any asset.
Always perform your own analysis and manage risk appropriately.
OXE MTF Support/Resistance+Demand/Supply Zone ArsenalOXE MTF Support/Resistance + Demand/Supply Zones Indicator
Your Complete Multi-Timeframe Zone Arsenal
This professional-grade indicator transforms your chart into a zone confluence powerhouse, simultaneously tracking high-probability price reaction areas across 5 timeframes (Daily, H4, H1, M15, M5) – giving you the institutional edge you need to dominate the markets.
🎯 What It Is
A sophisticated dual-system zone detector that identifies both:
Classic Support/Resistance levels using pivot point detection
Smart Money Demand/Supply zones triggered by Break-of-Structure (BOS) confirmations
Unlike basic S/R indicators, this tool employs institutional methodology – capturing order blocks and imbalance zones where smart money is positioned, not just where price bounced.
⚡ Core Capabilities
Multi-Timeframe Mastery
Track up to 5 timeframes simultaneously without switching charts
Identify confluence zones where multiple timeframe levels align
Customize which timeframes to display for clean, focused analysis
Intelligent Zone Management
Automatic zone validation – tracks when zones flip from resistance→support or supply→demand
Invalid zone filtering – hide broken/invalidated zones to focus only on active opportunities
Configurable zone limits – control the number of zones per timeframe (up to 8 each)
Smart Money Detection
BOS-confirmed zones – only marks demand/supply after break-of-structure confirmation
Precise zone timing – captures the exact candle that created the imbalance
Visual differentiation – dashed borders distinguish demand/supply from traditional S/R
Professional Dashboard
Real-time zone counter – shows active zones per timeframe at a glance
Filter status indicators – tracks which validation filters are enabled
Color-coded timeframe labels – instant visual organization
💰 How This Transforms Your Trading
1. Find High-Probability Entries
Enter trades at zones where multiple timeframes converge – when H4 demand aligns with Daily support, you've found institutional backing.
2. Stay on the Right Side of the Market
The zone flipping system shows you when market structure changes – a supply zone that flips to demand tells you the narrative has shifted bullish.
3. Eliminate Guesswork
No more wondering "is this level still valid?" The automatic invalidation tracking removes subjectivity – zones are either active (tradeable) or broken (ignored).
4. Scale Your Timeframe Analysis
Whether you're scalping M5 or swing trading Daily, access all relevant zones without the mental overhead of switching between charts and manually tracking levels.
5. Trade Like Institutions
By combining pivot-based S/R with BOS-confirmed order blocks, you're seeing where retail AND institutional money is positioned – giving you the complete picture.
🔥 Perfect For
Day traders seeking M15/H1 confluence for precise entries
Scalpers needing M5 zones with higher-timeframe confirmation
Swing traders looking for Daily/H4 zone alignment for position trades
ICT/SMC practitioners combining order blocks with traditional analysis
Any trader who values clean, validated, multi-timeframe zones over cluttered charts
🟡 GOLD 4H HUD v12 — Time-Safe Nuclear Edition🟡 GOLD 4H HUD v12 — Time-Safe Nuclear Edition
A full–scale Smart Money Concepts (SMC) analytics engine designed exclusively for XAUUSD on the 4-Hour timeframe.
This script combines market structure, liquidity, displacement, order blocks, imbalance, volume profile, SMT divergence, and institutional behavior modeling into a single unified HUD.
Built with a time-safe architecture, all structural elements (OB/FVG/Sweep) are stored by timestamp to minimize repainting and preserve event integrity.
📌 Core Features (12 Modules + Full HUD)
1 — Market Structure Engine
Automatically detects:
HH / HL / LH / LL
BOS (Break of Structure)
MSS (Market Structure Shift)
CHOCH (Change of Character)
Real swing pivots & trend state
2 — Sweep Engine (Liquidity Grab Detection)
Identifies institutional liquidity grabs:
Break + reclaim of highs/lows
ATR-filtered invalidation
Displacement-backed sweeps
3 — Time-Safe FVG Engine
Detects Bullish/Bearish Fair Value Gaps
ATR-tolerant FVG logic
Automatic right-extension
Auto-delete when filled or invalid
4 — Time-Safe Order Block Engine
Demand & Supply OB detection
Strength classification (Weak vs Strong)
FVG-overlap confirmation
Timestamp-locked (non-repainting)
5 — Volume Profile Engine (HVN / LVN / POC)
Real-time micro-profile:
High Volume Node (HVN)
Low Volume Node (LVN)
Point of Control (POC)
6 — SMT Engine (Gold vs DXY Divergence)
Smart Money Divergence built-in:
Bullish SMT
Bearish SMT
Directional confirmation with zero lag
7 — Displacement Engine
Measures institutional impulse:
Body-based impulse detection
Multi-leg continuation signals
FVG continuation moves
Generates displacement score
8 — Premium / Discount Model
Auto-classifies price into:
Discount (Buy zone)
Premium (Sell zone)
9 — SMC Trend Engine (Score-Based)
Combines 10+ factors:
Structure
FVG
OB power
Displacement
POC positioning
SMT conditions
Outputs:
BULL / BEAR / RANGE
Full scoring system
10 — Institutional Imbalance Model (IMB Engine)
Combines:
PD zones
Sweep direction
Displacement
SMT
OB strength
CHOCH/MSS
A complete institutional bias filter.
11 — Entry Engine (Signal Fusion Model)
Entry conditions fuse:
Sweep
CHOCH
Displacement
OB strength
FVG alignment
SMT confirmation
Also outputs:
Suggested SL/TP
Entry score
12 — Trendline Engine
Auto-draws:
HL → HL bullish trendlines
LH → LH bearish trendlines
+ Full Nuclear HUD
Displays:
Market structure
Trend direction
SMT / CHOCH / MSS
FVG / OB zones
HVN / LVN / POC
Liquidity strength
Entry model
Liquidity Magnet direction
SL/TP map
A complete institutional dashboard in one place.
⚠ Usage Requirement
This script is designed ONLY for the 4H timeframe.
✨ Summary
GOLD 4H HUD v12 — Time-Safe Nuclear Edition
is not just an indicator.
It is a full institutional-grade SMC analysis system, built specifically for Gold.
If you trade XAUUSD on the 4H timeframe —
this is your complete market intelligence HUD
Institutional Flow Engine (IFE) v1.7 PROInstitutional Flow Engine (IFE) v1.7 PRO — Description
The Institutional Flow Engine (IFE) is an intraday market-flow framework built around liquidity behavior, session timing and structural shifts. Instead of combining public indicators, IFE uses its own unified engine that monitors:
• Accumulation ranges formed during the early session
• Liquidity events when price reaches key levels and rejects
• Structural shifts based on pivot swings
• Momentum confirmation after structural breaks
• Higher-timeframe inefficiency zones (price speed / imbalance areas)
• Session-specific conditions for Core Session and Expansion Session
The objective is to provide a logical roadmap of how price transitions from accumulation → manipulation → expansion during the trading day.
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1. Session Framework
IFE operates using three phases:
1. Asia Accumulation Phase
- Builds the core accumulation range
- Builds an extended reference range used later by the Expansion Session
2. Pre-Core Phase
- Tracks a local intraday range before the main session
- Detects liquidity taps or sweeps of this range
3. Core Session (London)
- Primary signal window where the engine evaluates directional intent
4. Expansion Session (New York)
- Secondary session logic for continuation or reversal during the afternoon
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2. Liquidity Events and Key Levels
IFE identifies multiple types of liquidity behavior:
• Sweeps of the Asia accumulation range
• Sweeps of the extended reference range
• Sweeps of the pre-session intraday range
• Equal-high and equal-low clusters that attract price and later reject
A liquidity event is confirmed when price trades beyond a key level and then returns back into the range.
Users can decide whether:
• Liquidity events are required for signals
• Only the side where liquidity was taken should be traded
• Both sides can be considered
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3. Structural Shifts and Momentum Confirmation
The engine monitors local structure using pivot-based swing points. A directional shift occurs when price closes beyond a previous swing level.
This shift is validated only if accompanied by a momentum candle (a body significantly larger than recent average).
The user can select aggressive, standard, or defensive confirmation modes.
These momentum-based signals are independent from zone-based signals.
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4. Inefficiency / Imbalance Zones (Higher Timeframe Mapping)
IFE maps areas where price moved too quickly (inefficiency zones) on a higher timeframe.
These zones:
• Are detected using multiple gap-based models
• Have a maximum lifetime
• Are invalidated if price fully trades through
• Are visualized with dynamic boxes extended forward
Optional signal conditions allow:
• Tap + rejection within an active zone
• Session window confirmation
• Liquidity-based directional filters
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5. Equilibrium Filters (Optional)
IFE calculates an equilibrium level for each session based on the midpoint of either:
• The Asia accumulation range, or
• The most recent structural swing range
Users can restrict signals so that:
• Shorts only trigger above equilibrium
• Longs only trigger below equilibrium
This helps avoid entries in the inefficient half of the range.
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6. Signal Types
There are two main signal types inside each session:
1. Zone-Based Signals
- Price interacts with an active inefficiency zone
- Liquidity event is confirmed
- Price rejects the zone
- Session window is active
2. Momentum-Based Signals
- A structural shift is confirmed
- A momentum candle supports the move
- Liquidity/equilibrium conditions are met
- Session window is active
Long and short signals are plotted clearly on the chart with directional labels.
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7. Alerts
IFE includes alerts for:
• Zone-based long/short signals
• Momentum-based long/short signals
• Core Session events
• Expansion Session events
Each alert matches the exact visual signal on chart.
--------------------------------------------------------------------
8. Practical Use
IFE is designed for:
• Major indices (NAS100, ES, DAX)
• FX majors
• High-liquidity crypto pairs
Recommended workflow:
1. Observe how the Asia range forms initial liquidity.
2. Watch for liquidity grabs before the main session.
3. Use inefficiency zones as primary interest areas.
4. Use session timing as the main filter.
5. Apply your own risk management alongside the signals.
IFE is a structural mapping tool intended for experienced traders. It does not constitute financial advice.
FCPO MASTER v6 – Sideway + Breakout + OB + FVG (TUPLE SAFE)TL;DR cepat
1. Gunakan M5 untuk entry & OB/FVG confirmation.
2. Gunakan M15 untuk confirm trend/false breakout.
3. Gunakan H1 untuk bias arah (overall market).
4. Entry hanya bila signal + OB/FVG/candle rejection (script buatkan).
5. SL 5–8 tick, TP 10–25 tick ikut setup (sideway vs breakout).
6. Follow checklist setiap trade — jangan lompat.
________________________________________
Setup awal (1–2 min)
1. Pasang script FCPO Sideway MASTER – OB + Imbalance + Confirmation di TradingView.
2. Timeframes: buka M5, M15, H1 (susun 3 chart atau 1 chart multi-timeframe).
3. Input default: ATR14, Breakout Buffer 5 tick, RangeLen 20, ADX14, TP12, SL8. (Kau boleh tweak nanti).
4. Aktifkan alerts pada BUY Confirm / SELL Confirm / Sideway Buy / Sideway Sell.
________________________________________
Step-by-step trading process
1) Mulakan dengan H1 — tentukan bias HTF
• Lihat H1 untuk jawapan: Trend Up / Down / Sideway.
• Rule ringkas:
o ADX H1 > 20 + price above H1 EMA → bias Bull
o ADX H1 > 20 + price below H1 EMA → bias Bear
o ADX H1 < 20 → market HTF sideway (no strong bias)
Kenapa: H1 bagi kau idea “kalau breakout pada M5, patut follow atau tolak”.
________________________________________
2) Pergi ke M15 — confirm trend & valid breakout
• M15 kena setuju dengan idea breakout.
o Untuk strong breakout: M15 kena tunjuk candle close di atas/bawah range + volume naik.
o Kalau M5 breakout tapi M15 tak setuju (M15 masih sideway) → treat as fakeout. Jangan masuk.
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3) M5 — cari entry & confirmation (OB/FVG + candle)
• M5 adalah tempat kau buat keputusan masuk.
• Tunggu script keluarkan Sideway Buy/Sell atau Breakout Buy/Sell.
• CONFIRM entry mesti ada sekurang-kurangnya 1 dari:
o Bull/Bear Order Block searah signal (script detect).
o FVG / Imbalance zone dipenuhi & price retest.
o Candle rejection (pinbar / bearish/bullish engulfing) pada zone.
Jika tiada confirmation → no trade.
________________________________________
4) Checklist sebelum tekan Buy/Sell (MUST)
• H1 bias tidak melawan trade (prefer sama arah).
• M15 confirm breakout / trend or neutral.
• Script keluarkan signal (sideway or breakout).
• OB or FVG atau candle rejection ada.
• ATR kenaikan jika breakout (untuk breakout trade).
• Volume spike jika breakout.
• Risk:SL <= 2% akaun (position sizing).
Kalau semua ticked → boleh entry.
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5) Setting SL / TP & position sizing
• Sideway (scalp): SL = 5–8 tick, TP = 8–12 tick.
• Breakout (trend): SL = 8–12 tick, TP = 15–25+ tick (trail later).
• Position sizing: Risk per trade 1–2%.
o Lot size = (Account Risk RM × 1 tick value) / (SL ticks × tickValue) — (kalau kau gunakan fixed tick value, adjust ikut lot).
(Script tunjuk SL & TP label — follow itu.)
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6) Entry types
• A. Sideway Reversal (M5)
o Signal: Sideway Buy / Sideway Sell
o Confirm: OB/FVG or rejection candle at range bottom/top
o Trade: scalp target 8–12 tick, tight SL 5–8 tick
• B. Breakout (M5 entry, M15 confirm)
o Signal: Breakout Buy/Sell (Strong)
o Confirm: ATR expanding + volume spike + M15 alignment
o Trade: trend follow, TP 15–25 tick, trailing stop active
• C. Retest Entry
o Breakout happens, price returns to retest range / OB / FVG → wait for rejection candle then enter. Safer.
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7) Trailing & exit rules
• Jika useTrail = true script plots trailing stop (ATR × multiplier).
• Exit rules:
1. Hit TP → close.
2. Hit SL → close.
3. If trailing stop hit → close.
4. If opposing confirmed signal muncul (e.g., SELL confirm while long) → consider close early.
5. If H1 bias flips strongly vs trade → tighten stop or close.
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8) Multiple signals & scaling
• Never add to losing position (no averaging down).
• If want scale-in on confirmed trend: add 1 partial size after price moves +10–12 tick in favor and shows continuation candle + no bearish OB/FVG.
• Keep aggregated risk within your max (2–3%).
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9) Example trade walkthrough (concrete)
• RangeHigh = 4065, RangeLow = 4035 (contoh).
• Market sideway M5.
Case A — Sideway Sell:
1. Price touches 4064–4065, script shows sidewaySell.
2. Lihat OB: ada bear OB zone di 4062–4066 → confirm.
3. Candle rejection (bearish pinbar) muncul → enter SELL M5.
4. Set SL = 5 tick above rangeHigh = 4070, TP = 10 tick → 4055.
5. Trail jika price turun > 8 tick: aktifkan trailing.
6. Close at TP or trail/SL.
Case B — Breakout Buy:
1. Price closes above 4065 + 5 tick buffer = 4070 on M5. Script shows trueBreakUp.
2. M15 shows candle close above M15 resistance + volume spike → confirm.
3. Enter BUY, SL = 8 tick below entry, TP initial 20 tick, trail with ATR×1.5.
4. Move stop to breakeven after +10 tick, scale out half at +12 tick, leave rest to trail.
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10) Journal & review
• Semua trade: record entry time, TF, reason (which confirmations), SL/TP, result, lesson.
• Weekly review: check which confirmation worked best (OB vs FVG vs candle) and tweak settings.
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11) Tweaks / optimisations cepat
• Jika terlalu banyak false sideway signals → kurangkan touchDist ke 2 tick.
• Kalau fakeout breakout banyak → tambah tickBuf ke 6–8.
• Nak lebih konservatif → cuma trade breakout yang juga setuju M15.
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12) Alerts & execution (practical)
• Pasang alert pada BUY Confirm / SELL Confirm (script).
• Kalau kau guna broker yang support one-click order, siap sediakan template order (SL/TP default).
• Kalau manual, bila alert masuk: buka M5, cepat confirm OB/FVG & candle rejection → entry.
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Quick reference table (handy)
• TF utama entry: M5
• Confirm mid-TF: M15
• Bias HTF: H1
• Sideway SL/TP: SL 5–8, TP 8–12
• Breakout SL/TP: SL 8–12, TP 15–25+
• Mandatory confirmation: (Script signal) + (OB or FVG or candle)
Flow Dynamics Pro [ChartNation]Flow Dynamics Pro - Institutional Order Flow Zones
Detect high-probability institutional rejection zones with advanced volume analysis and confluence scoring.
Flow Dynamics Pro identifies institutional order flow zones where smart money enters and defends positions. Unlike traditional order blocks or supply/demand indicators, this tool combines multiple confirmation factors into a single confluence score, helping you focus on the highest-quality setups.
🎯 KEY FEATURES
Institutional Zone Detection
Volume spike analysis (customizable threshold)
Rejection wick detection (upper/lower wick ratios)
Market structure validation (swing high/low alignment)
Multi-factor confluence scoring (0-100 scale)
Visual Volume Distribution
Bull/bear volume split displayed inside each zone
See the exact buying vs selling pressure at institutional levels
Percentage breakdowns for quick analysis
Toggle on/off based on preference
Smart Zone Management
Automatic zone invalidation when broken with volume
Zone test tracking (shows how many times zones held)
Visual strengthening (borders thicken after successful tests)
Overlap prevention (maintains minimum spacing between zones)
Maximum zone limit (keeps chart clean)
Confluence Scoring System
Zones are scored 0-100 based on:
Volume Strength (30 points) - How significant was the volume spike
Market Structure (25 points) - Alignment with swing points
Zone Quality (25 points) - Wick ratio and pressure imbalance
Size Quality (20 points) - Optimal zone size relative to ATR
Zones are categorized as:
⚡ PREMIUM (80+) - Highest quality setups
🔥 STRONG (60-79) - Solid institutional zones
✓ MODERATE (40-59) - Valid but lower confluence
Timeframe Adaptive
Automatically adjusts detection sensitivity based on timeframe:
On 1H and lower: Stricter requirements (reduces noise)
On 4H and higher: Standard sensitivity (catches major zones)
Works on all timeframes from 1-minute to Monthly
Multi-Timeframe Context
Display higher timeframe zones for broader market context
Customizable HTF timeframe selection
Dashed visualization to distinguish from current timeframe zones
Comprehensive Alerts
Premium zone created (score 80+)
Price entering zone
Price exiting zone
Zone tested successfully
Zone invalidated
⚙️ SETTINGS OVERVIEW
Detection Settings
Volume Spike Threshold (default: 1.2x)
Minimum Wick Ratio (default: 0.3)
Structure Validation toggle
Detection Lookback period
Invalidation Settings
Require volume for invalidation (toggle)
Invalidation volume threshold (default: 1.2x)
Customizable to match your trading style
Display Settings
Maximum zones to display (default: 8)
Show/hide labels
Show/hide volume data
Volume distribution toggle
Label size adjustment (Small/Normal/Large)
Minimum zone spacing % (prevents overlaps)
Minimum confluence score filter (default: 55)
Visual Customization
Bullish zone color and opacity
Bearish zone color and opacity
Border colors
Multi-timeframe zone colors
📊 HOW TO USE
For Swing Traders (4H, Daily)
Focus on PREMIUM zones (score 80+)
Look for zones with multiple successful tests
Enter on retests with confirmation
Use HTF zones for broader context
For Intraday Traders (1H, 15m)
Use higher confluence minimum (60-65)
Increase zone spacing to reduce clutter
Focus on zones with clear volume distribution
Combine with price action for entries
Zone Test Interpretation
Tested 0x: Fresh zone, untested
Tested 1-2x: Gaining strength
Tested 3+x: Highly defended level (thicker borders)
Volume Distribution Guide
80%+ on one side: Strong directional bias
60-70% dominance: Moderate bias
50-50 split: Contested area, use caution
🔧 BEST PRACTICES
Combine with trend: Trade zones in direction of higher timeframe trend
Wait for confirmation: Don't enter blindly at zone touch
Respect invalidation: When zones break with volume, they're done
Use confluence scores: Prioritize scores 70+ for highest win rate
Manage spacing: Adjust spacing % if chart feels cluttered
Check timeframe: Lower timeframes may need stricter settings
🎓 UNDERSTANDING THE INDICATOR
What are Institutional Zones?
Areas where large players (institutions, market makers, smart money) have entered positions and actively defend them. These show up as:
High volume rejection wicks
Multiple tests that hold
Clear buying/selling pressure imbalance
Why Confluence Scoring?
Not all zones are equal. The 0-100 scoring system helps you quickly identify which zones have the most confirmation factors aligned, saving time and improving trade selection.
Why Zone Spacing Matters
Too many overlapping zones create analysis paralysis. The spacing filter ensures you see only distinct, meaningful levels.
📈 TECHNICAL DETAILS
Indicator Type: Overlay
Max Boxes: 500
Max Labels: 500
Pine Script Version: 6
Real-time Updates: Yes
Alerts: 5 types available
Repainting: Zones finalize on bar close
🚀 GET STARTED
Add indicator to chart
Adjust confluence minimum (55-65 recommended)
Set volume threshold for your instrument (1.2-1.5)
Customize colors to match your theme
Enable alerts for your preferred signals
Trade with proper risk management
💡 TIPS
Start with default settings and adjust based on results
Higher timeframes = more reliable zones
Premium zones (80+) have best risk/reward
Tested zones (3+) show strong institutional defense
Use zone invalidation as stop-loss reference
Flow Dynamics Pro is part of the ChartNation indicator suite - delivering institutional-grade tools for serious traders.
Delta+CVD&CVD CandlesDelta + CVD & CVD Candles
Order-flow indicator combining Delta (Ask–Bid), Cumulative Volume Delta (CVD), and a unique CVD-based synthetic candle system. Shows buy/sell pressure, volume aggressiveness, and momentum shifts with optional Delta histogram, CVD line, and CVD+Delta combined candles. Useful for scalping, intraday trading, divergence detection, and understanding buyer/seller dominance.
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📘 Overview
The Delta + CVD & CVD Candles Indicator combines multiple order-flow tools into one clean visual package. It displays:
• Delta (Ask–Bid) to measure aggressive buying/selling
• Cumulative Volume Delta (CVD) to track accumulated pressure
• Combined CVD Candles showing synthetic candles built entirely from order-flow data
This indicator helps traders read market intent, find momentum shifts, and detect absorption or hidden buying/selling without needing Level-2 data.
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📊 Features
1. Delta (Ask-Bid) Histogram
Shows buying vs selling pressure per candle.
• Green = Buyers (Ask > Bid)
• Red = Sellers (Bid > Ask)
2. CVD (Cumulative Delta) Line
Tracks whether buyers or sellers dominate over time.
Useful for spotting divergences and trend strength.
3. Delta + CVD Combined Candles
Synthetic candles built from order-flow:
• Candle body = change in CVD
• Wicks = size of Delta imbalance
• Colors = green (bullish), red (bearish)
These candles reveal aggressive buying/selling much more clearly than price candles.
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🛠 Inputs & Options
• Show/Hide Delta Histogram
• Show/Hide CVD Line
• Show/Hide Combined CVD Candles
• Bull Color
• Bear Color
• CVD Line Color
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📈 How to Trade With It
• Rising CVD + bullish Delta → Strong up momentum
• Falling CVD + bearish Delta → Strong down momentum
• Price HH but CVD failing → Bearish divergence
• Price LL but CVD not making LL → Bullish divergence
• Long wick in combined candle → High imbalance (aggressive buyers/sellers)
Great for scalping, day trading, and momentum confirmation.
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⚠️ Notes
• Uses TradingView’s volume feed (not Level-2 depth).
• Works on all markets and timeframes.
• Volume accuracy depends on exchange data.
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✔️ Recommended Use-Cases
• Intraday trading
• Volume/Delta analysis
• Divergence trading
• Identifying exhaustion and absorption
• Understanding buyer/seller strength visually
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👤 Credits
Paraskumarpatel5026@gmail.com
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Market Maker EngineThe Core Concept: "Weighted Probability"
Most indicators just look for one thing (like lines crossing). This indicator is different. It acts like a judge scoring a gymnastics competition. It looks at 5 different factors simultaneously and assigns points to them.
It only gives you a CALL or PUT signal if the total confidence score is 80% or higher.
The "Brain"; Scoring Trades
1. Smart Money Concept; (30pts)
What it looks for: ICT Fair Value Gaps (FVG).
Why: This is the most heavily weighted factor because it identifies where institutions (banks/hedge funds) have left a "footprint" of aggressive buying or selling.
Logic: If price creates a gap that isn't filled by the next candle, it signals a strong imbalance.
2.Volume Anomalies (25 Points)
What it looks for: Is the volume statistically unusual? (Z-Score > 2.0).
Why: Retail traders trade with standard volume. "Smart Money" trades with massive volume spikes.
Logic: If volume is 2x higher than the average and price is moving in your direction, it adds 25 points.
3.Momentum Alignment (20 Points)
What it looks for: RSI and MACD working together.
Why: You don't want to catch a falling knife.
Logic:
Bull: RSI > 50 AND MACD Line > Signal Line.
Bear: RSI < 50 AND MACD Line < Signal Line.
4.Trend Filter (15 Points)
What it looks for: The 50-period Exponential Moving Average (EMA).
Why: "The trend is your friend."
Logic: It checks if the price is simply above (Bullish) or below (Bearish) the 50 EMA.
5.The "Squeeze" (10 Points)
What it looks for: Bollinger Bands contracting inside Keltner Channels.
Why: This signals "pent-up energy." When volatility gets low (squeeze), a violent explosive move usually follows.
HOW TO READ AND USE THIS INDICATOR
🟢 GREEN ARROW (CALL): The algorithm is at least 80% confident that price is going UP. (Structure + Volume + Momentum are aligned).
🔴 RED ARROW (PUT): The algorithm is at least 80% confident that price is going DOWN.
🟡 YELLOW CANDLES: These are "Whale Alerts." The volume on this specific candle is statistically abnormal. Even if there is no arrow, pay attention—big money is active here.
⚫ BLACK SCOREBOARD: On the very last candle, you will see a text box (e.g., Bull: 65%). This shows you the live calculation. If you see it climbing (40%... 60%... 75%...), a signal might be imminent.
Recommend Strategy;
This script should be favorable to Day Trade
Timeframe: Stick to the 10-minute or 15-minute chart. (The noise on the 1-minute might trigger false 80% scores).
The "Yellow" Rule: If you see a Yellow Candle without an arrow, wait. It means volume is high, but the trend/structure isn't ready yet.
Exit Strategy: Since this is an entry indicator, you should look to take profits at the next logical Support/Resistance level or when the Momentum (RSI) reverses.
Ultimate S&D (Pro Edition)**Institutional Supply & Demand (Auto-Cleaning & Freshness Tracking)**
This indicator is designed for Price Action and Futures traders who require a clean, objective view of Institutional Supply and Demand zones. unlike standard indicators that clutter the chart with historic levels, this script focuses on **"Smart Mitigation"**—automatically removing zones that have been invalidated to keep your chart pristine.
### Key Features:
**1. 🏦 Institutional Imbalance Detection**
The script identifies **ERC (Extended Range Candles)** and momentum shifts to locate true institutional interest. It automatically marks the "Base" preceding the explosive move as a valid zone.
**2. 🧹 Smart Auto-Invalidation (Clean Chart Logic)**
Most S&D indicators leave old, broken zones on the chart. This script actively monitors price action:
* **Supply Zones:** Automatically deleted if price breaks above the zone's high.
* **Demand Zones:** Automatically deleted if price breaks below the zone's low.
* **Result:** You only see active, defendable levels.
**3. 🔄 Zone Freshness Tracking (Fresh vs. Tested)**
Visual cues help you gauge the probability of a setup:
* **Fresh Zones:** Solid borders with darker colors. (High Probability)
* **Tested Zones:** Once price touches a zone but holds, the zone turns **Dashed** and lighter in color, labeled as "(Tested)". (Lower Probability / Caution required)
**4. 🏷️ Dynamic Timeframe Labeling**
Zones are automatically labeled with the chart's timeframe (e.g., "1H Demand", "15m Supply"), making it perfect for Multi-Timeframe Analysis (MTF) and sharing screenshots.
**5. 🔔 Integrated Alerts**
Never miss an entry. You can set alerts to trigger the moment price enters a Fresh or Tested zone.
---
### ⚙️ Settings Guide:
* **Imbalance Strength:** Controls how strict the filter is. Higher values (e.g., 4.0) only show the strongest institutional moves. Lower values (e.g., 2.0) show more local zones.
* **Lookback Period:** How many bars are used to calculate average volatility.
* **Zone Extension:** How far the boxes extend to the right (auto-limited to prevent clutter).
### 🎯 How to use:
Recommended for use as a "Confluence Tool." Use your daily bias and trend analysis first, then use this script to identify precise entry zones on 1H, 15m, or 5m charts.
*For educational purposes only. Trade responsibly.*
ULTIMATE ORDER FLOW SYSTEM🔥 ULTIMATE ORDER FLOW SYSTEM
Overview
This comprehensive order flow analysis tool combines **Volume Profile**, **Cumulative Delta**, and **Large Order Detection** to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react.
📊 Core Components & Methodology
🔥 ULTIMATE ORDER FLOW SYSTEM
Overview
This comprehensive order flow analysis tool combines Volume Profile, Cumulative Delta, and Large Order Detection to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react.
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📊 Core Components & Methodology
1. Volume Profile Analysis
The script constructs a horizontal volume profile by:
• Dividing the price range into configurable rows (default: 20)
• Accumulating volume at each price level over a lookback period (default: 50 bars)
• Separating buy volume (green bars close > open) from sell volume (red bars)
• Identifying three critical levels:
o POC (Point of Control): Price level with highest traded volume - acts as a strong magnet
o VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone
o HVN (High Volume Nodes): Resistance zones where institutions accumulated positions
o LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets
Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance.
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2. Cumulative Delta (Order Flow)
Tracks the running total of buying vs selling pressure:
• Bar Delta: Difference between buy and sell volume per candle
• Cumulative Delta: Sum of all bar deltas - shows net directional pressure
• Delta Moving Average: Smoothed delta (20-period) to identify trend
• Delta Divergences:
o Bullish: Price makes lower low, but delta makes higher low (absorption at bottom)
o Bearish: Price makes higher high, but delta makes lower high (exhaustion at top)
How It Works: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations.
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3. Large Order Detection
Identifies institutional-sized orders in real-time:
• Compares current bar volume to 20-period moving average
• Flags orders exceeding 2.5x average volume (configurable multiplier)
• Distinguishes bullish (green circles below) vs bearish (red circles above) large orders
Rationale: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals.
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🎯 Trading Signal Logic
Combined Setup Criteria
The script generates SHORT and LONG signals when multiple conditions align:
SHORT Signal Requirements:
1. Price reaches an HVN resistance zone (within 0.2%)
2. Large sell order detected (volume spike + red candle)
3. Cumulative delta is bearish OR bearish divergence present
4. 10-bar cooldown between signals (prevents overtrading)
LONG Signal Requirements:
1. Price reaches an HVN support zone
2. Large buy order detected (volume spike + green candle)
3. Cumulative delta is bullish OR bullish divergence present
4. 10-bar cooldown enforced
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🔧 Customization Options
Setting - Purpose - Recommendation
Volume Profile Rows - Granularity of level detection - 20 (balanced)
Lookback Period - Historical data analyzed - 50 bars (intraday), 200 (swing)
Large Order Multiplier - Sensitivity to volume spikes - 2.5x (standard), 3.5x (conservative)
HVN Threshold - Resistance zone detection - 1.3 (default)
LVN Threshold - Target zone identification - 0.6 (default)
Divergence Lookback - Pivot detection period - 5 bars (responsive)
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📈 Dashboard Indicators
The real-time panel displays:
• POC: Current Point of Control price
• Location: Whether price is at HVN resistance
• Orders: Current large buy/sell activity
• Cumulative Δ: Net order flow value + trend direction
• Divergence: Active bullish/bearish divergences
• Bar Strength: % of candle volume that's directional (>65% = strong)
• SETUP: Current trade signal (LONG/SHORT/WAIT)
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🎨 Visual System
• Yellow POC Line: Highest volume level - primary pivot
• Blue Value Area Box: Fair value zone (VAH to VAL)
• Red HVN Zones: Resistance/support from institutional accumulation
• Green LVN Zones: Low-liquidity targets for quick moves
• Volume Bars: Green (buy pressure) vs Red (sell pressure) distribution
• Triangles: LONG (green up) and SHORT (red down) entry signals
• Diamonds: Divergence warnings (cyan=bullish, fuchsia=bearish)
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💡 How This Script Is Unique
Unlike standalone volume profile or delta indicators, this script:
1. Synthesizes three complementary methods - volume structure, order flow momentum, and liquidity detection
2. Requires multi-factor confirmation - signals only trigger when price, volume, and delta align at key zones
3. Adapts to market regime - delta filters ensure you're trading with the dominant order flow direction
4. Provides context, not just signals - the dashboard helps you understand why a setup is forming
________________________________________
⚙️ Best Practices
Timeframes:
• 5-15 min: Scalping (use 30-50 bar lookback)
• 1-4 hour: Swing trading (use 100-200 bar lookback)
Risk Management:
• Enter on signal candle close
• Stop loss: Beyond nearest HVN/LVN zone
• Target 1: Next LVN level
• Target 2: Opposite value area boundary
Filters:
• Avoid signals during major news events
• Require bar delta strength >65% for aggressive entries
• Wait for delta MA cross confirmation in ranging markets
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🚨 Alerts Available
• Long Setup Trigger
• Short Setup Trigger
• Bullish/Bearish Divergence Detection
• Large Buy/Sell Order Execution
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📚 Educational Context
This methodology is based on principles used by professional order flow traders:
• Market Profile Theory: Volume distribution reveals fair value
• Tape Reading: Large orders show institutional intent
• Auction Theory: Price seeks areas of liquidity imbalance (LVN zones)
The script automates pattern recognition that discretionary traders spend years learning to identify manually.
________________________________________
⚠️ Disclaimer
This indicator is a trading tool, not a trading system. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results.
________________________________________
Version: 6 (Pine Script)
Type: Overlay + Separate Pane (Delta Panel)
Resource Usage: Moderate (500 bars history, 500 lines/boxes)
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For questions or support, please comment below. If you find this script valuable, please boost and favorite! 🚀
1. Volume Profile Analysis
The script constructs a horizontal volume profile by:
- Dividing the price range into configurable rows (default: 20)
- Accumulating volume at each price level over a lookback period (default: 50 bars)
- Separating buy volume (green bars close > open) from sell volume (red bars)
- Identifying three critical levels:
- POC (Point of Control): Price level with highest traded volume - acts as a strong magnet
- VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone
- HVN (High Volume Nodes): Resistance zones where institutions accumulated positions
- LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets
Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance.
---
2. Cumulative Delta (Order Flow)
Tracks the running total of buying vs selling pressure:
- **Bar Delta**: Difference between buy and sell volume per candle
- **Cumulative Delta**: Sum of all bar deltas - shows net directional pressure
- **Delta Moving Average**: Smoothed delta (20-period) to identify trend
- **Delta Divergences**:
- **Bullish**: Price makes lower low, but delta makes higher low (absorption at bottom)
- **Bearish**: Price makes higher high, but delta makes lower high (exhaustion at top)
**How It Works**: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations.
---
### 3. **Large Order Detection**
Identifies **institutional-sized orders** in real-time:
- Compares current bar volume to 20-period moving average
- Flags orders exceeding 2.5x average volume (configurable multiplier)
- Distinguishes bullish (green circles below) vs bearish (red circles above) large orders
**Rationale**: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals.
---
## 🎯 Trading Signal Logic
### Combined Setup Criteria
The script generates **SHORT** and **LONG** signals when multiple conditions align:
**SHORT Signal Requirements:**
1. Price reaches an HVN resistance zone (within 0.2%)
2. Large sell order detected (volume spike + red candle)
3. Cumulative delta is bearish OR bearish divergence present
4. 10-bar cooldown between signals (prevents overtrading)
**LONG Signal Requirements:**
1. Price reaches an HVN support zone
2. Large buy order detected (volume spike + green candle)
3. Cumulative delta is bullish OR bullish divergence present
4. 10-bar cooldown enforced
---
## 🔧 Customization Options
| Setting | Purpose | Recommendation |
|---------|---------|----------------|
| **Volume Profile Rows** | Granularity of level detection | 20 (balanced) |
| **Lookback Period** | Historical data analyzed | 50 bars (intraday), 200 (swing) |
| **Large Order Multiplier** | Sensitivity to volume spikes | 2.5x (standard), 3.5x (conservative) |
| **HVN Threshold** | Resistance zone detection | 1.3 (default) |
| **LVN Threshold** | Target zone identification | 0.6 (default) |
| **Divergence Lookback** | Pivot detection period | 5 bars (responsive) |
---
## 📈 Dashboard Indicators
The real-time panel displays:
- **POC**: Current Point of Control price
- **Location**: Whether price is at HVN resistance
- **Orders**: Current large buy/sell activity
- **Cumulative Δ**: Net order flow value + trend direction
- **Divergence**: Active bullish/bearish divergences
- **Bar Strength**: % of candle volume that's directional (>65% = strong)
- **SETUP**: Current trade signal (LONG/SHORT/WAIT)
---
## 🎨 Visual System
- **Yellow POC Line**: Highest volume level - primary pivot
- **Blue Value Area Box**: Fair value zone (VAH to VAL)
- **Red HVN Zones**: Resistance/support from institutional accumulation
- **Green LVN Zones**: Low-liquidity targets for quick moves
- **Volume Bars**: Green (buy pressure) vs Red (sell pressure) distribution
- **Triangles**: LONG (green up) and SHORT (red down) entry signals
- **Diamonds**: Divergence warnings (cyan=bullish, fuchsia=bearish)
---
## 💡 How This Script Is Unique
Unlike standalone volume profile or delta indicators, this script:
1. **Synthesizes three complementary methods** - volume structure, order flow momentum, and liquidity detection
2. **Requires multi-factor confirmation** - signals only trigger when price, volume, and delta align at key zones
3. **Adapts to market regime** - delta filters ensure you're trading with the dominant order flow direction
4. **Provides context, not just signals** - the dashboard helps you understand *why* a setup is forming
---
## ⚙️ Best Practices
**Timeframes:**
- 5-15 min: Scalping (use 30-50 bar lookback)
- 1-4 hour: Swing trading (use 100-200 bar lookback)
**Risk Management:**
- Enter on signal candle close
- Stop loss: Beyond nearest HVN/LVN zone
- Target 1: Next LVN level
- Target 2: Opposite value area boundary
**Filters:**
- Avoid signals during major news events
- Require bar delta strength >65% for aggressive entries
- Wait for delta MA cross confirmation in ranging markets
---
## 🚨 Alerts Available
- Long Setup Trigger
- Short Setup Trigger
- Bullish/Bearish Divergence Detection
- Large Buy/Sell Order Execution
---
## 📚 Educational Context
This methodology is based on principles used by professional order flow traders:
- **Market Profile Theory**: Volume distribution reveals fair value
- **Tape Reading**: Large orders show institutional intent
- **Auction Theory**: Price seeks areas of liquidity imbalance (LVN zones)
The script automates pattern recognition that discretionary traders spend years learning to identify manually.
---
## ⚠️ Disclaimer
This indicator is a **trading tool, not a trading system**. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results.
---
**Version**: 6 (Pine Script)
**Type**: Overlay + Separate Pane (Delta Panel)
**Resource Usage**: Moderate (500 bars history, 500 lines/boxes)
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*For questions or support, please comment below. If you find this script valuable, please boost and favorite!* 🚀
Piku Pips📌 Piku Pips — Multi-Confluence Smart Signal System (EMA + Supertrend + Volume Profile + ATR Trailing + SR + RSI Climax Engine)
Piku Pips is a complete multi-confluence trading system designed for scalpers, intraday traders, and swing traders who rely on precision entries and institutional-grade confirmation layers.
This indicator combines trend, momentum, volatility, volume imbalance, structure breaks, smart money pivots, and exhaustion events—into a single unified charting system.
It does NOT repaint, supports alerts, and works across all assets (crypto, forex, indices, stocks).
🔥 What Makes This Indicator Special?
Piku Pips is built on stacked confluences instead of single-indicator signals.
Each signal is only printed when multiple conditions align, significantly increasing accuracy and reducing noise.
It includes:
✔ Trend Identification
Fast & Slow EMA cross
SuperTrend with custom ATR & factor
Parabolic SAR for micro-trend confirmation
ATR-based trailing stop engine (dual version for Buy & Sell)
✔ Momentum Confirmation
RSI Midline model
HH/LL structure detection
Bull/Bear volume imbalance model
✔ Smart Volume Analysis
Bullish vs Bearish VWMA volume
Flat-volume filters
RSI + Volume Spike + MFI exhaustion detection (Climax Module)
✔ Institutional Structure Mapping
Dynamic Support & Resistance
Automatic Zone Strength Ranking
Breakout detection with zone coloring
Pivot-based structure scanning
✔ Exhaustion + Divergence Engine (Climax Module)
RSI / Stochastic RSI hybrid
Macro trend smoothing (EMA/RMA/SMA/WMA selectable)
High-precision RSI divergence detection (HH/LH and LL/HL)
Volume spike detection
Buy Climax (potential top)
Sell Climax (potential bottom)
This module acts like a “smart momentum brain” that identifies major reversals.
🎯 Signal Logic (Simplified)
🔹 Buy Signal (Green Triangle)
Triggered when:
Fast EMA crosses above Slow EMA
Higher High structure forms
RSI > midline or crosses above it
Volume profile is bullish
SuperTrend is bullish (direction < 0)
🔹 Sell Signal (Red Triangle)
Triggered when:
Fast EMA crosses below Slow EMA
Lower Low structure forms
RSI < midline or crosses below it
Volume profile is bearish
SuperTrend is bearish (direction > 0)
🔸 Secondary ATR Signals (Orange & Maroon)
Uses Heikin-Ashi ATR trailing stop
Detects micro-shifts in trend momentum
Works excellent in scalping timeframes
🧠 Support & Resistance Engine
The script builds dynamic SR zones based on:
Pivot clustering
Channel width filtering
Strength scoring
Automated sorting and plotting
Zones:
Red tint = Resistance
Green tint = Support
Gray tint = Neutral / In-Play
Alerts trigger on clean SR breaks.
⚡ Climax Module (Exhaustion System)
This system overlays major exhaustion points:
🔻 Buy Climax
High-volume upward exhaustion → potential top.
🔺 Sell Climax
High-volume downward exhaustion → potential bottom.
🔼 RSI Divergences
Bullish divergence labeled "RSI⬆"
Bearish divergence labeled "RSI⬇"
Combined, these give early insight into possible reversals.
🛠 Inputs Overview
📌 Trend Inputs
Fast EMA Length
Slow EMA Length
SuperTrend ATR + Factor
SAR multipliers
Buy/Sell ATR trailing stop parameters
📌 Momentum Inputs
RSI length / midline
Bull/Bear volume variance filter
HH/LL confirmation
📌 Structure Inputs
Pivot sensitivity
Max SR Zones
Loopback length
Zone strength minimum
📌 Climax Module Inputs
RSI / Stochastic lengths
Smoothing method (EMA, SMA, RMA, WMA)
Macro trend slope settings
Pivot sensitivity for divergence
Volume spike multiplier
MFI thresholds
Bull/Bear RSI levels
📈 How to Use Piku Pips
Best Use-Cases:
Scalping (1m–15m)
Intraday (15m–1H)
Swing trading (4H–1D)
Crypto / Forex / Indices / Stocks
Recommended Approach
Trade in direction of EMA + Supertrend + Macro RSI regime.
Enter when Piku Buy/Sell signal aligns with the trend.
Use SR zones as targets or invalidation levels.
Watch Climax signals for tops & bottoms.
Use divergence signals for early reversals.
🔔 Alerts Included
Buy Signal
Sell Signal
ATR Buy / Sell
Buy Climax
Sell Climax
RSI Divergence (bullish & bearish)
All-Signals alert
⚠️ Disclaimer
This indicator is created for educational purposes only and does not constitute financial advice.
Trading involves risk. Do your own research and backtesting before using any tool in live markets.
Timeframe Fast EMA Slow EMA ATR Period Factor RSI Length Overbought/Oversold
5 Min 9 21 10 2 8 80 / 20
15 Min 10 25 10 2.5 10 75/25
1 Hour 20 50 14 3 12 70/30
4 Hour 21 50 14 3 14 70/30
1 Day 20 100 14 3.5 14 70/30
Please use this settings for accurate results
Algorithm Predator - ProAlgorithm Predator - Pro: Advanced Multi-Agent Reinforcement Learning Trading System
Algorithm Predator - Pro combines four specialized market microstructure agents with a state-of-the-art reinforcement learning framework . Unlike traditional indicator mashups, this system implements genuine machine learning to automatically discover which detection strategies work best in current market conditions and adapts continuously without manual intervention.
Core Innovation: Rather than forcing traders to interpret conflicting signals, this system uses 15 different multi-armed bandit algorithms and a full reinforcement learning stack (Q-Learning, TD(λ) with eligibility traces, and Policy Gradient with REINFORCE) to learn optimal agent selection policies. The result is a self-improving system that gets smarter with every trade.
Target Users: Swing traders, day traders, and algorithmic traders seeking systematic signal generation with mathematical rigor. Suitable for stocks, forex, crypto, and futures on liquid instruments (>100k daily volume).
Why These Components Are Combined
The Fundamental Problem
No single indicator works consistently across all market regimes. What works in trending markets fails in ranging conditions. Traditional solutions force traders to manually switch indicators (slow, error-prone) or interpret all signals simultaneously (cognitive overload).
This system solves the problem through automated meta-learning: Deploy multiple specialized agents designed for specific market microstructure conditions, then use reinforcement learning to discover which agent (or combination) performs best in real-time.
Why These Specific Four Agents?
The four agents provide orthogonal failure mode coverage —each agent's weakness is another's strength:
Spoofing Detector - Optimal in consolidation/manipulation; fails in trending markets (hedged by Exhaustion Detector)
Exhaustion Detector - Optimal at trend climax; fails in range-bound markets (hedged by Liquidity Void)
Liquidity Void - Optimal pre-breakout compression; fails in established trends (hedged by Mean Reversion)
Mean Reversion - Optimal in low volatility; fails in strong trends (hedged by Spoofing Detector)
This creates complete market state coverage where at least one agent should perform well in any condition. The bandit system identifies which one without human intervention.
Why Reinforcement Learning vs. Simple Voting?
Traditional consensus systems have fatal flaws: equal weighting assumes all agents are equally reliable (false), static thresholds don't adapt, and no learning means past mistakes repeat indefinitely.
Reinforcement learning solves this through the exploration-exploitation tradeoff: Continuously test underused agents (exploration) while primarily relying on proven winners (exploitation). Over time, the system builds a probability distribution over agent quality reflecting actual market performance.
Mathematical Foundation: Multi-armed bandit problem from probability theory, where each agent is an "arm" with unknown reward distribution. The goal is to maximize cumulative reward while efficiently learning each arm's true quality.
The Four Trading Agents: Technical Explanation
Agent 1: 🎭 Spoofing Detector (Institutional Manipulation Detection)
Theoretical Basis: Market microstructure theory on order flow toxicity and information asymmetry. Based on research by Easley, López de Prado, and O'Hara on high-frequency trading manipulation.
What It Detects:
1. Iceberg Orders (Hidden Liquidity Absorption)
Method: Monitors volume spikes (>2.5× 20-period average) with minimal price movement (<0.3× ATR)
Formula: score += (close > open ? -2.5 : 2.5) when volume > vol_avg × 2.5 AND abs(close - open) / ATR < 0.3
Interpretation: Large volume without price movement indicates institutional absorption (buying) or distribution (selling) using hidden orders
Signal Logic: Contrarian—fade false breakouts caused by institutional manipulation
2. Spoofing Patterns (Fake Liquidity via Layering)
Method: Analyzes candlestick wick-to-body ratios during volume spikes
Formula: if upper_wick > body × 2 AND volume_spike: score += 2.0
Mechanism: Spoofing creates large wicks (orders pulled before execution) with volume evidence
Signal Logic: Wick direction indicates trapped participants; trade against the failed move
3. Post-Manipulation Reversals
Method: Tracks volume decay after manipulation events
Formula: if volume > vol_avg × 3 AND volume / volume < 0.3: score += (close > open ? -1.5 : 1.5)
Interpretation: Sharp volume drop after manipulation indicates exhaustion of manipulative orders
Why It Works: Institutional manipulation creates detectable microstructure anomalies. While retail traders see "mysterious reversals," this agent quantifies the order flow patterns causing them.
Parameter: i_spoof (sensitivity 0.5-2.0) - Controls detection threshold
Best Markets: Consolidations before breakouts, London/NY overlap windows, stocks with institutional ownership >70%
Agent 2: ⚡ Exhaustion Detector (Momentum Failure Analysis)
Theoretical Basis: Technical analysis divergence theory combined with VPIN reversals from market microstructure literature.
What It Detects:
1. Price-RSI Divergence (Momentum Deceleration)
Method: Compares 5-bar price ROC against RSI change
Formula: if price_roc > 5% AND rsi_current < rsi : score += 1.8
Mathematics: Second derivative detecting inflection points
Signal Logic: When price makes higher highs but momentum makes lower highs, expect mean reversion
2. Volume Exhaustion (Buying/Selling Climax)
Method: Identifies strong price moves (>5% ROC) with declining volume (<-20% volume ROC)
Formula: if price_roc > 5 AND vol_roc < -20: score += 2.5
Interpretation: Price extension without volume support indicates retail chasing while institutions exit
3. Momentum Deceleration (Acceleration Analysis)
Method: Compares recent 3-bar momentum to prior 3-bar momentum
Formula: deceleration = abs(mom1) < abs(mom2) × 0.5 where momentum significant (> ATR)
Signal Logic: When rate of price change decelerates significantly, anticipate directional shift
Why It Works: Momentum is lagging, but momentum divergence is leading. By comparing momentum's rate of change to price, this agent detects "weakening conviction" before reversals become obvious.
Parameter: i_momentum (sensitivity 0.5-2.0)
Best Markets: Strong trends reaching climax, parabolic moves, instruments with high retail participation
Agent 3: 💧 Liquidity Void Detector (Breakout Anticipation)
Theoretical Basis: Market liquidity theory and order book dynamics. Based on research into "liquidity holes" and volatility compression preceding expansion.
What It Detects:
1. Bollinger Band Squeeze (Volatility Compression)
Method: Monitors Bollinger Band width relative to 50-period average
Formula: bb_width = (upper_band - lower_band) / middle_band; triggers when < 0.6× average
Mathematical Foundation: Regression to the mean—low volatility precedes high volatility
Signal Logic: When volatility compresses AND cumulative delta shows directional bias, anticipate breakout
2. Volume Profile Gaps (Thin Liquidity Zones)
Method: Identifies sharp volume transitions indicating few limit orders
Formula: if volume < vol_avg × 0.5 AND volume < vol_avg × 0.5 AND volume > vol_avg × 1.5
Interpretation: Sudden volume drop after spike indicates price moved through order book to low-opposition area
Signal Logic: Price accelerates through low-liquidity zones
3. Stop Hunts (Liquidity Grabs Before Reversals)
Method: Detects new 20-bar highs/lows with immediate reversal and rejection wick
Formula: if new_high AND close < high - (high - low) × 0.6: score += 3.0
Mechanism: Market makers push price to trigger stop-loss clusters, then reverse
Signal Logic: Enter reversal after stop-hunt completes
Why It Works: Order book theory shows price moves fastest through zones with minimal liquidity. By identifying these zones before major moves, this agent provides early entry for high-reward breakouts.
Parameter: i_liquidity (sensitivity 0.5-2.0)
Best Markets: Range-bound pre-breakout setups, volatility compression zones, instruments prone to gap moves
Agent 4: 📊 Mean Reversion (Statistical Arbitrage Engine)
Theoretical Basis: Statistical arbitrage theory, Ornstein-Uhlenbeck mean-reverting processes, and pairs trading methodology applied to single instruments.
What It Detects:
1. Z-Score Extremes (Standard Deviation Analysis)
Method: Calculates price distance from 20-period and 50-period SMAs in standard deviation units
Formula: zscore_20 = (close - SMA20) / StdDev(50)
Statistical Interpretation: Z-score >2.0 means price is 2 standard deviations above mean (97.5th percentile)
Trigger Logic: if abs(zscore_20) > 2.0: score += zscore_20 > 0 ? -1.5 : 1.5 (fade extremes)
2. Ornstein-Uhlenbeck Process (Mean-Reverting Stochastic Model)
Method: Models price as mean-reverting stochastic process: dx = θ(μ - x)dt + σdW
Implementation: Calculates spread = close - SMA20, then z-score of spread vs. spread distribution
Formula: ou_signal = (spread - spread_mean) / spread_std
Interpretation: Measures "tension" pulling price back to equilibrium
3. Correlation Breakdown (Regime Change Detection)
Method: Compares 50-period price-volume correlation to 10-period correlation
Formula: corr_breakdown = abs(typical_corr - recent_corr) > 0.5
Enhancement: if corr_breakdown AND abs(zscore_20) > 1.0: score += zscore_20 > 0 ? -1.2 : 1.2
Why It Works: Mean reversion is the oldest quantitative strategy (1970s pairs trading at Morgan Stanley). While simple, it remains effective because markets exhibit periodic equilibrium-seeking behavior. This agent applies rigorous statistical testing to identify when mean reversion probability is highest.
Parameter: i_statarb (sensitivity 0.5-2.0)
Best Markets: Range-bound instruments, low-volatility periods (VIX <15), algo-dominated markets (forex majors, index futures)
Multi-Armed Bandit System: 15 Algorithms Explained
What Is a Multi-Armed Bandit Problem?
Origin: Named after slot machines ("one-armed bandits"). Imagine facing multiple slot machines, each with unknown payout rates. How do you maximize winnings?
Formal Definition: K arms (agents), each with unknown reward distribution with mean μᵢ. Goal: Maximize cumulative reward over T trials. Challenge: Balance exploration (trying uncertain arms to learn quality) vs. exploitation (using known-best arm for immediate reward).
Trading Application: Each agent is an "arm." After each trade, receive reward (P&L). Must decide which agent to trust for next signal.
Algorithm Categories
Bayesian Approaches (probabilistic, optimal for stationary environments):
Thompson Sampling
Bootstrapped Thompson Sampling
Discounted Thompson Sampling
Frequentist Approaches (confidence intervals, deterministic):
UCB1
UCB1-Tuned
KL-UCB
SW-UCB (Sliding Window)
D-UCB (Discounted)
Adversarial Approaches (robust to non-stationary environments):
EXP3-IX
Hedge
FPL-Gumbel
Reinforcement Learning Approaches (leverage learned state-action values):
Q-Values (from Q-Learning)
Policy Network (from Policy Gradient)
Simple Baseline:
Epsilon-Greedy
Softmax
Key Algorithm Details
Thompson Sampling (DEFAULT - RECOMMENDED)
Theoretical Foundation: Bayesian decision theory with conjugate priors. Published by Thompson (1933), rediscovered for bandits by Chapelle & Li (2011).
How It Works:
Model each agent's reward distribution as Beta(α, β) where α = wins, β = losses
Each step, sample from each agent's beta distribution: θᵢ ~ Beta(αᵢ, βᵢ)
Select agent with highest sample: argmaxᵢ θᵢ
Update winner's distribution after observing outcome
Mathematical Properties:
Optimality: Achieves logarithmic regret O(K log T) (proven optimal)
Bayesian: Maintains probability distribution over true arm means
Automatic Balance: High uncertainty → more exploration; high certainty → exploitation
⚠️ CRITICAL APPROXIMATION: This is a pseudo-random approximation of true Thompson Sampling. True implementation requires random number generation from beta distributions, which Pine Script doesn't provide. This version uses Box-Muller transform with market data (price/volume decimal digits) as entropy source. While not mathematically pure, it maintains core exploration-exploitation balance and learns agent preferences effectively.
When To Use: Best all-around choice. Handles non-stationary markets reasonably well, balances exploration naturally, highly sample-efficient.
UCB1 (Upper Confidence Bound)
Formula: UCB_i = reward_mean_i + sqrt(2 × ln(total_pulls) / pulls_i)
Interpretation: First term (exploitation) + second term (exploration bonus for less-tested arms)
Mathematical Properties:
Deterministic : Always selects same arm given same state
Regret Bound: O(K log T) — same optimality as Thompson Sampling
Interpretable: Can visualize confidence intervals
When To Use: Prefer deterministic behavior, want to visualize uncertainty, stable markets
EXP3-IX (Exponential Weights - Adversarial)
Theoretical Foundation: Adversarial bandit algorithm. Assumes environment may be actively hostile (worst-case analysis).
How It Works:
Maintain exponential weights: w_i = exp(η × cumulative_reward_i)
Select agent with probability proportional to weights: p_i = (1-γ)w_i/Σw_j + γ/K
After outcome, update with importance weighting: estimated_reward = observed_reward / p_i
Mathematical Properties:
Adversarial Regret: O(sqrt(TK log K)) even if environment is adversarial
No Assumptions: Doesn't assume stationary or stochastic reward distributions
Robust: Works even when optimal arm changes continuously
When To Use: Extreme non-stationarity, don't trust reward distribution assumptions, want robustness over efficiency
KL-UCB (Kullback-Leibler Upper Confidence Bound)
Theoretical Foundation: Uses KL-divergence instead of Hoeffding bounds. Tighter confidence intervals.
Formula (conceptual): Find largest q such that: n × KL(p||q) ≤ ln(t) + 3×ln(ln(t))
Mathematical Properties:
Tighter Bounds: KL-divergence adapts to reward distribution shape
Asymptotically Optimal: Better constant factors than UCB1
Computationally Intensive: Requires iterative binary search (15 iterations)
When To Use: Maximum sample efficiency needed, willing to pay computational cost, long-term trading (>500 bars)
Q-Values & Policy Network (RL-Based Selection)
Unique Feature: Instead of treating agents as black boxes with scalar rewards, these algorithms leverage the full RL state representation .
Q-Values Selection:
Uses learned Q-values: Q(state, agent_i) from Q-Learning
Selects agent via softmax over Q-values for current market state
Advantage: Selects based on state-conditional quality (which agent works best in THIS market state)
Policy Network Selection:
Uses neural network policy: π(agent | state, θ) from Policy Gradient
Direct policy over agents given market features
Advantage: Can learn non-linear relationships between market features and agent quality
When To Use: After 200+ RL updates (Q-Values) or 500+ updates (Policy Network) when models converged
Machine Learning & Reinforcement Learning Stack
Why Both Bandits AND Reinforcement Learning?
Critical Distinction:
Bandits treat agents as contextless black boxes: "Agent 2 has 60% win rate"
Reinforcement Learning adds state context: "Agent 2 has 60% win rate WHEN trend_score > 2 and RSI < 40"
Power of Combination: Bandits provide fast initial learning with minimal assumptions. RL provides state-dependent policies for superior long-term performance.
Component 1: Q-Learning (Value-Based RL)
Algorithm: Temporal Difference Learning with Bellman equation.
State Space: 54 discrete states formed from:
trend_state = {0: bearish, 1: neutral, 2: bullish} (3 values)
volatility_state = {0: low, 1: normal, 2: high} (3 values)
RSI_state = {0: oversold, 1: neutral, 2: overbought} (3 values)
volume_state = {0: low, 1: high} (2 values)
Total states: 3 × 3 × 3 × 2 = 54 states
Action Space: 5 actions (No trade, Agent 1, Agent 2, Agent 3, Agent 4)
Total state-action pairs: 54 × 5 = 270 Q-values
Bellman Equation:
Q(s,a) ← Q(s,a) + α ×
Parameters:
α (learning rate): 0.01-0.50, default 0.10 - Controls step size for updates
γ (discount factor): 0.80-0.99, default 0.95 - Values future rewards
ε (exploration): 0.01-0.30, default 0.10 - Probability of random action
Update Mechanism:
Position opens with state s, action a (selected agent)
Every bar position is open: Calculate floating P&L → scale to reward
Perform online TD update
When position closes: Perform terminal update with final reward
Gradient Clipping: TD errors clipped to ; Q-values clipped to for stability.
Why It Works: Q-Learning learns "quality" of each agent in each market state through trial and error. Over time, builds complete state-action value function enabling optimal state-dependent agent selection.
Component 2: TD(λ) Learning (Temporal Difference with Eligibility Traces)
Enhancement Over Basic Q-Learning: Credit assignment across multiple time steps.
The Problem TD(λ) Solves:
Position opens at t=0
Market moves favorably at t=3
Position closes at t=8
Question: Which earlier decisions contributed to success?
Basic Q-Learning: Only updates Q(s₈, a₈) ← reward
TD(λ): Updates ALL visited state-action pairs with decayed credit
Eligibility Trace Formula:
e(s,a) ← γ × λ × e(s,a) for all s,a (decay all traces)
e(s_current, a_current) ← 1 (reset current trace)
Q(s,a) ← Q(s,a) + α × TD_error × e(s,a) (update all with trace weight)
Lambda Parameter (λ): 0.5-0.99, default 0.90
λ=0: Pure 1-step TD (only immediate next state)
λ=1: Full Monte Carlo (entire episode)
λ=0.9: Balance (recommended)
Why Superior: Dramatically faster learning for multi-step tasks. Q-Learning requires many episodes to propagate rewards backwards; TD(λ) does it in one.
Component 3: Policy Gradient (REINFORCE with Baseline)
Paradigm Shift: Instead of learning value function Q(s,a), directly learn policy π(a|s).
Policy Network Architecture:
Input: 12 market features
Hidden: None (linear policy)
Output: 5 actions (softmax distribution)
Total parameters: 12 features × 5 actions + 5 biases = 65 parameters
Feature Set (12 Features):
Price Z-score (close - SMA20) / ATR
Volume ratio (volume / vol_avg - 1)
RSI deviation (RSI - 50) / 50
Bollinger width ratio
Trend score / 4 (normalized)
VWAP deviation
5-bar price ROC
5-bar volume ROC
Range/ATR ratio - 1
Price-volume correlation (20-period)
Volatility ratio (ATR / ATR_avg - 1)
EMA50 deviation
REINFORCE Update Rule:
θ ← θ + α × ∇log π(a|s) × advantage
where advantage = reward - baseline (variance reduction)
Why Baseline? Raw rewards have high variance. Subtracting baseline (running average) centers rewards around zero, reducing gradient variance by 50-70%.
Learning Rate: 0.001-0.100, default 0.010 (much lower than Q-Learning because policy gradients have high variance)
Why Policy Gradient?
Handles 12 continuous features directly (Q-Learning requires discretization)
Naturally maintains exploration through probability distribution
Can converge to stochastic optimal policy
Component 4: Ensemble Meta-Learner (Stacking)
Architecture: Level-1 meta-learner combines Level-0 base learners (Q-Learning, TD(λ), Policy Gradient).
Three Meta-Learning Algorithms:
1. Simple Average (Baseline)
Final_prediction = (Q_prediction + TD_prediction + Policy_prediction) / 3
2. Weighted Vote (Reward-Based)
weight_i ← 0.95 × weight_i + 0.05 × (reward_i + 1)
3. Adaptive Weighting (Gradient-Based) — RECOMMENDED
Loss Function: L = (y_true - ŷ_ensemble)²
Gradient: ∂L/∂weight_i = -2 × (y_true - ŷ_ensemble) × agent_contribution_i
Updates weights via gradient descent with clipping and normalization
Why It Works: Unlike simple averaging, meta-learner discovers which base learner is most reliable in current regime. If Policy Gradient excels in trending markets while Q-Learning excels in ranging, meta-learner learns these patterns and weights accordingly.
Feature Importance Tracking
Purpose: Identify which of 12 features contribute most to successful predictions.
Update Rule: importance_i ← 0.95 × importance_i + 0.05 × |feature_i × reward|
Use Cases:
Feature selection: Drop low-importance features
Market regime detection: Importance shifts reveal regime changes
Agent tuning: If VWAP deviation has high importance, consider boosting agents using VWAP
RL Position Tracking System
Critical Innovation: Proper reinforcement learning requires tracking which decisions led to outcomes.
State Tracking (When Signal Validates):
active_rl_state ← current_market_state (0-53)
active_rl_action ← selected_agent (1-4)
active_rl_entry ← entry_price
active_rl_direction ← 1 (long) or -1 (short)
active_rl_bar ← current_bar_index
Online Updates (Every Bar Position Open):
floating_pnl = (close - entry) / entry × direction
reward = floating_pnl × 10 (scale to meaningful range)
reward = clip(reward, -5.0, 5.0)
Update Q-Learning, TD(λ), and Policy Gradient
Terminal Update (Position Close):
Final Q-Learning update (no next Q-value, terminal state)
Update meta-learner with final result
Update agent memory
Clear position tracking
Exit Conditions:
Time-based: ≥3 bars held (minimum hold period)
Stop-loss: 1.5% adverse move
Take-profit: 2.0% favorable move
Market Microstructure Filters
Why Microstructure Matters
Traditional technical analysis assumes fair, efficient markets. Reality: Markets have friction, manipulation, and information asymmetry. Microstructure filters detect when market structure indicates adverse conditions.
Filter 1: VPIN (Volume-Synchronized Probability of Informed Trading)
Theoretical Foundation: Easley, López de Prado, & O'Hara (2012). "Flow Toxicity and Liquidity in a High-Frequency World."
What It Measures: Probability that current order flow is "toxic" (informed traders with private information).
Calculation:
Classify volume as buy or sell (close > close = buy volume)
Calculate imbalance over 20 bars: VPIN = |Σ buy_volume - Σ sell_volume| / Σ total_volume
Compare to moving average: toxic = VPIN > VPIN_MA(20) × sensitivity
Interpretation:
VPIN < 0.3: Normal flow (uninformed retail)
VPIN 0.3-0.4: Elevated (smart money active)
VPIN > 0.4: Toxic flow (informed institutions dominant)
Filter Logic:
Block LONG when: VPIN toxic AND price rising (don't buy into institutional distribution)
Block SHORT when: VPIN toxic AND price falling (don't sell into institutional accumulation)
Adaptive Threshold: If VPIN toxic frequently, relax threshold; if rarely toxic, tighten threshold. Bounded .
Filter 2: Toxicity (Kyle's Lambda Approximation)
Theoretical Foundation: Kyle (1985). "Continuous Auctions and Insider Trading."
What It Measures: Price impact per unit volume — market depth and informed trading.
Calculation:
price_impact = (close - close ) / sqrt(Σ volume over 10 bars)
impact_zscore = (price_impact - impact_mean) / impact_std
toxicity = abs(impact_zscore)
Interpretation:
Low toxicity (<1.0): Deep liquid market, large orders absorbed easily
High toxicity (>2.0): Thin market or informed trading
Filter Logic: Block ALL SIGNALS when toxicity > threshold. Most dangerous when price breaks from VWAP with high toxicity.
Filter 3: Regime Filter (Counter-Trend Protection)
Purpose: Prevent counter-trend trades during strong trends.
Trend Scoring:
trend_score = 0
trend_score += close > EMA8 ? +1 : -1
trend_score += EMA8 > EMA21 ? +1 : -1
trend_score += EMA21 > EMA50 ? +1 : -1
trend_score += close > EMA200 ? +1 : -1
Range:
Regime Classification:
Strong Bull: trend_score ≥ +3 → Block all SHORT signals
Strong Bear: trend_score ≤ -3 → Block all LONG signals
Neutral: -2 ≤ trend_score ≤ +2 → Allow both directions
Filter 4: Liquidity Boost (Signal Enhancer)
Unique: Unlike other filters (which block), this amplifies signals during low liquidity.
Logic: if volume < vol_avg × 0.7: agent_scores × 1.2
Why It Works: Low liquidity often precedes explosive moves (breakouts). By increasing agent sensitivity during compression, system catches pre-breakout signals earlier.
Technical Implementation & Approximations
⚠️ Critical Approximations Required by Pine Script
1. Thompson Sampling: Pseudo-Random Beta Distribution
Academic Standard: True random sampling from beta distributions using cryptographic RNG
This Implementation: Box-Muller transform for normal distribution using market data (price/volume decimal digits) as entropy source, then scale to beta distribution mean/variance
Impact: Not cryptographically random, may have subtle biases in specific price ranges, but maintains correct mean and approximate variance. Sufficient for bandit agent selection.
2. VPIN: Simplified Volume Classification
Academic Standard: Lee-Ready algorithm or exchange-provided aggressor flags with tick-by-tick data
This Implementation: Bar-based classification: if close > close : buy_volume += volume
Impact: 10-15% precision loss. Works well in directional markets, misclassifies in choppy conditions. Still captures order flow imbalance signal.
3. Policy Gradient: Simplified Per-Action Updates
Academic Standard: Full softmax gradient updating all actions (selected action UP, others DOWN proportionally)
This Implementation: Only updates selected action's weights
Impact: Valid approximation for small action spaces (5 actions). Slower convergence than full softmax but still learns optimal policy.
4. Kyle's Lambda: Simplified Price Impact
Academic Standard: Regression over multiple time scales with signed order flow
This Implementation: price_impact = Δprice_10 / sqrt(Σvolume_10); z_score calculation
Impact: 15-20% precision loss. No proper signed order flow. Still detects informed trading signals at extremes (>2σ).
5. Other Simplifications:
Hawkes Process: Fixed exponential decay (0.9) not MLE-optimized
Entropy: Ratio approximation not true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Feature Engineering: 12 features vs. potential 100+ with polynomial interactions
RL Hybrid Updates: Both online and terminal (non-standard but empirically effective)
Overall Precision Loss Estimate: 10-15% compared to academic implementations with institutional data feeds.
Practical Trade-off: For retail trading with OHLCV data, these approximations provide 90%+ of the edge while maintaining full transparency, zero latency, no external dependencies, and runs on any TradingView plan.
How to Use: Practical Guide
Initial Setup (5 Minutes)
Select Trading Mode: Start with "Balanced" for most users
Enable ML/RL System: Toggle to TRUE, select "Full Stack" ML Mode
Bandit Configuration: Algorithm: "Thompson Sampling", Mode: "Switch" or "Blend"
Microstructure Filters: Enable all four filters, enable "Adaptive Microstructure Thresholds"
Visual Settings: Enable dashboard (Top Right), enable all chart visuals
Learning Phase (First 50-100 Signals)
What To Monitor:
Agent Performance Table: Watch win rates develop (target >55%)
Bandit Weights: Should diverge from uniform (0.25 each) after 20-30 signals
RL Core Metrics: "RL Updates" should increase when position open
Filter Status: "Blocked" count indicates filter activity
Optimization Tips:
Too few signals: Lower min_confidence to 0.25, increase agent sensitivities to 1.1-1.2
Too many signals: Raise min_confidence to 0.35-0.40, decrease agent sensitivities to 0.8-0.9
One agent dominates (>70%): Consider "Lock Agent" feature
Signal Interpretation
Dashboard Signal Status:
⚪ WAITING FOR SIGNAL: No agent signaling
⏳ ANALYZING...: Agent signaling but not confirmed
🟡 CONFIRMING 2/3: Building confirmation (2 of 3 bars)
🟢 LONG ACTIVE : Validated long entry
🔴 SHORT ACTIVE : Validated short entry
Kill Zone Boxes: Entry price (triangle marker), Take Profit (Entry + 2.5× ATR), Stop Loss (Entry - 1.5× ATR). Risk:Reward = 1:1.67
Risk Management
Position Sizing:
Risk per trade = 1-2% of capital
Position size = (Capital × Risk%) / (Entry - StopLoss)
Stop-Loss Placement:
Initial: Entry ± 1.5× ATR (shown in kill zone)
Trailing: After 1:1 R:R achieved, move stop to breakeven
Take-Profit Strategy:
TP1 (2.5× ATR): Take 50% off
TP2 (Runner): Trail stop at 1× ATR or use opposite signal as exit
Memory Persistence
Why Save Memory: Every chart reload resets the system. Saving learned parameters preserves weeks of learning.
When To Save: After 200+ signals when agent weights stabilize
What To Save: From Memory Export panel, copy all alpha/beta/weight values and adaptive thresholds
How To Restore: Enable "Restore From Saved State", input all values into corresponding fields
What Makes This Original
Innovation 1: Genuine Multi-Armed Bandit Framework
This implements 15 mathematically rigorous bandit algorithms from academic literature (Thompson Sampling from Chapelle & Li 2011, UCB family from Auer et al. 2002, EXP3 from Auer et al. 2002, KL-UCB from Garivier & Cappé 2011). Each algorithm maintains proper state, updates according to proven theory, and converges to optimal behavior. This is real learning, not superficial parameter changes.
Innovation 2: Full Reinforcement Learning Stack
Beyond bandits learning which agent works best globally, RL learns which agent works best in each market state. After 500+ positions, system builds 54-state × 5-action value function (270 learned parameters) capturing context-dependent agent quality.
Innovation 3: Market Microstructure Integration
Combines retail technical analysis with institutional-grade microstructure metrics: VPIN from Easley, López de Prado, O'Hara (2012), Kyle's Lambda from Kyle (1985), Hawkes Processes from Hawkes (1971). These detect informed trading, manipulation, and liquidity dynamics invisible to technical analysis.
Innovation 4: Adaptive Threshold System
Dynamic quantile-based thresholds: Maintains histogram of each agent's score distribution (24 bins, exponentially decayed), calculates 80th percentile threshold from histogram. Agent triggers only when score exceeds its own learned quantile. Proper non-parametric density estimation automatically adapts to instrument volatility, agent behavior shifts, and market regime changes.
Innovation 5: Episodic Memory with Transfer Learning
Dual-layer architecture: Short-term memory (last 20 trades, fast adaptation) + Long-term memory (condensed episodes, historical patterns). Transfer mechanism consolidates knowledge when STM reaches threshold. Mimics hippocampus → neocortex consolidation in human memory.
Limitations & Disclaimers
General Limitations
No Predictive Guarantee: Pattern recognition ≠ prediction. Past performance ≠ future results.
Learning Period Required: Minimum 50-100 bars for reliable statistics. Initial performance may be suboptimal.
Overfitting Risk: System learns patterns in historical data. May not generalize to unprecedented conditions.
Approximation Limitations: See technical implementation section (10-15% precision loss vs. academic standards)
Single-Instrument Limitation: No multi-asset correlation, sector context, or VIX integration.
Forward-Looking Bias Disclaimer
CRITICAL TRANSPARENCY: The RL system uses an 8-bar forward-looking window for reward calculation.
What This Means: System learns from rewards incorporating future price information (bars 101-108 relative to entry at bar 100).
Why Acceptable:
✅ Signals do NOT look ahead: Entry decisions use only data ≤ entry bar
✅ Learning only: Forward data used for optimization, not signal generation
✅ Real-time mirrors backtest: In live trading, system learns identically
⚠️ Implication: Dashboard "Agent Win%" reflects this 8-bar evaluation. Real-time performance may differ slightly if positions held longer, slippage/fees not captured, or market microstructure changes.
Risk Warnings
No Guarantee of Profit: All trading involves risk of loss
System Failures: Bugs possible despite extensive testing
Market Conditions: Optimized for liquid markets (>100k daily volume). Performance degrades in illiquid instruments, major news events, flash crashes
Broker-Specific Issues: Execution slippage, commission/fees, overnight financing costs
Appropriate Use
This Indicator Is:
✅ Entry trigger system
✅ Risk management framework (stop/target)
✅ Adaptive agent selection engine
✅ Learning system that improves over time
This Indicator Is NOT:
❌ Complete trading strategy (requires position sizing, portfolio management)
❌ Replacement for fundamental analysis
❌ Guaranteed profit generator
❌ Suitable for complete beginners without training
Recommended Complementary Analysis: Market context (support/resistance), volume profile, fundamental catalysts, correlation with related instruments, broader market regime
Recommended Settings by Instrument
Stocks (Large Cap, >$1B):
Mode: Balanced | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling, Switch
Agent Sensitivity: Spoofing 1.0-1.2, Exhaustion 0.9-1.1, Liquidity 0.8-1.0, StatArb 1.1-1.3
Microstructure: All enabled, VPIN 1.2, Toxicity 1.5 | Timeframe: 15min-1H
Forex Majors (EURUSD, GBPUSD):
Mode: Balanced to Conservative | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling, Blend
Agent Sensitivity: Spoofing 0.8-1.0, Exhaustion 0.9-1.1, Liquidity 0.7-0.9, StatArb 1.2-1.5
Microstructure: All enabled, VPIN 1.0-1.1, Toxicity 1.3-1.5 | Timeframe: 5min-30min
Crypto (BTC, ETH):
Mode: Aggressive to Balanced | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling OR EXP3-IX
Agent Sensitivity: Spoofing 1.2-1.5, Exhaustion 1.1-1.3, Liquidity 1.2-1.5, StatArb 0.7-0.9
Microstructure: All enabled, VPIN 1.4-1.6, Toxicity 1.8-2.2 | Timeframe: 15min-4H
Futures (ES, NQ, CL):
Mode: Balanced | ML/RL: Enabled, Full Stack | Bandit: UCB1 or Thompson Sampling
Agent Sensitivity: All 1.0-1.2 (balanced)
Microstructure: All enabled, VPIN 1.1-1.3, Toxicity 1.4-1.6 | Timeframe: 5min-30min
Conclusion
Algorithm Predator - Pro synthesizes academic research from market microstructure theory, reinforcement learning, and multi-armed bandit algorithms. Unlike typical indicator mashups, this system implements 15 mathematically rigorous bandit algorithms, deploys a complete RL stack (Q-Learning, TD(λ), Policy Gradient), integrates institutional microstructure metrics (VPIN, Kyle's Lambda), adapts continuously through dual-layer memory and meta-learning, and provides full transparency on approximations and limitations.
The system is designed for serious algorithmic traders who understand that no indicator is perfect, but through proper machine learning, we can build systems that improve over time and adapt to changing markets without manual intervention.
Use responsibly. Risk disclosure applies. Past performance ≠ future results.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
GoldilocksTrader – Institutional Zones + Smart Money Market ModeThe GoldilocksTrader – Smart Money Trading System is a powerful institutional-grade tool designed for traders who want to follow real liquidity, identify institutional zones, and accurately read Smart Money market structure.
This indicator automatically detects Supply & Demand Zones, plots Institutional Pivot Levels, builds dynamic fade-strength heatmaps, and labels the current Market Mode (ACCUMULATE, DISTRIBUTE, WAIT)—all powered by a clean, real-time algorithm that updates with every candle.
This system helps you understand where banks, hedge funds, and institutions are likely to defend price, accumulate positions, or engineer liquidity sweeps. It makes complex Smart Money concepts simple, visual, and trader-friendly.
🧠 Core Features
✔ Institutional Supply & Demand Zones (auto-detected from swing pivots)
✔ Smart Money fade-strength heatmap using multi-layered boxes
✔ Market Mode Detection:
• ACCUMULATE – Smart Money loading long positions
• DISTRIBUTE – Smart Money unloading into premium levels
• WAIT – Neutral / imbalance zones
✔ EMA 9/21 Trend Filters
✔ VWAP Institutional Bias Filter
✔ Nearest Above/Below Liquidity Zones with clean readability
✔ Adjustable Transparency & Zone Thickness
✔ Compact On-Chart Legend (optional)
✔ Extremely lightweight, low-lag, optimized for all markets/timeframes
✔ Works for Forex, Crypto, Stocks, Indices, Futures, Commodities
📈 Trading Concepts Covered
This indicator is built around world-class concepts used by top proprietary desks and Smart Money traders, including:
ICT (Inner Circle Trader) Supply/Demand
Liquidity Zones & Institutional Order Blocks
Wyckoff Accumulation / Distribution
Imbalance & Fair Value Behavior (FVG-style fades)
Market Maker Models (MMXM + Premium/Discount Zones)
Pivot-based liquidity mapping
VWAP Institutional Bias
Trend Continuation vs. Reversal Zones
If you trade SMC, ICT, Wyckoff, Smart Money, Algo-based models, or institutional liquidity, this indicator is a perfect companion.
🚀 How It Helps You Trade
🔹 Identify hidden institutional levels where real accumulation or distribution occurs
🔹 Avoid bad trades by staying out of “WAIT” zones where most of the retail market enters.
🔹 Time entries during premium vs. discount pricing
🔹 Understand where price is expected to react, reverse, or continue
🔹 Visualize institutional pressure with fade-strength heatmaps
🔹 Combine with your own strategy to increase precision and confidence
🎨 Clean, Professional Visualization
Zones auto-extend to the left for historical context
Fade opacity increases or decreases depending on zone strength
Market Mode label plotted dynamically near relevant price zones
Optional compact legend for fast reading
All elements can be toggled and customized to your style.
⭐ Created by GoldilocksTrader™
For more institutional-level tools—including the new and soon to be popular "GoldilocksTrader Buy-Sell Signals with Built-In Optimizer"—search:
👉 “GoldilocksTrader” on TradingView
👉 Visit GoldilocksTrader.com for premium systems & education
Follow the institutions.
Trade Smart.
Trade Goldilocks™..."it's just right"
ICT Trading SuiteThe ICT Trading Suite is a complete price-action toolkit designed for traders who follow ICT concepts such as Fair Value Gaps (FVGs), Order Blocks (OBs), Supply & Demand Zones, Market Structure pivots, Liquidity Zones, and Moving Averages.
This indicator combines multiple institutional concepts into a single clean, optimized, high-performance script — allowing you to see the market the same way smart money does.
Each module can be toggled on/off to match your personal strategy.
🔥 FEATURE SET
1️⃣ Moving Averages (Fully Customisable)
5 MA slots
Multiple MA types: EMA, SMA, RMA, WMA, HMA, VWMA
Custom colours & visibility toggles
Supports all timeframes
Ideal for bias recognition and trend filtering.
2️⃣ Fair Value Gaps (FVG) – ICT 3-Candle Model
The script detects bullish and bearish FVGs using the classic ICT logic:
Bullish FVG → high < low
Bearish FVG → low > high
Features:
Automatic gap detection
Custom colours for up/down FVGs
CE (consequent encroachment) line
Optional deletion when filled
Extend FVGs dynamically
Lookback days filter
FVG blocks automatically update until price fills the imbalance.
3️⃣ Supply & Demand Zones (Swing-Based)
Built from confirmed swing highs/lows using ta.pivothigh and ta.pivotlow.
Features:
ATR-based zone thickness
Zone overlap filtering
Auto-cleaning oldest zones
POI (Point of Interest) marker
3 types of arrays:
Supply zone boxes
Demand zone boxes
POI midline boxes
Zones extend 100 bars by default and update dynamically.
Zones are deleted instantly when price breaks them (converted into BOS behavior).
4️⃣ Smart Money Order Blocks (Simple Engulfing Pattern)
OBs are detected using the classic engulfing model:
Bullish OB
Bearish candle → Engulfed by bullish candle where
close > high
Bearish OB
Bullish candle → Engulfed by bearish candle where
close < low
Each OB stores:
Original top/bottom
Current top/bottom
POI line (optional)
Engulfing candle structure
Mitigation state
Features:
Dynamic boundaries (OB shrinks as price mitigates)
POI line update
Automatic deletion (or recolour) when completely mitigated
Limit how many OBs stay on chart
Support for adding HTF OBs later
This creates very clean and very accurate ICT order blocks.
5️⃣ Liquidity / Vector Zones (Volume-Spread Analysis)
A built-in PVSRA-style logic marks areas of institutional activity.
Vector candles detected using:
Volume ≥ 200% of average
Or candle spread × volume ≥ highest in last 10 bars
Medium-volume vectors (150%) also included
Colour-coded zones extend to the right
Auto-cleanup once price clears the zone
Useful for detecting areas where algorithms (MMXs) aggressively buy/sell.
6️⃣ Pivot Levels
Multiple pivot methods supported:
Traditional
Fibonacci
Woodie
Classic
DM
Camarilla
Features:
Auto / Daily / Weekly / Monthly / Quarterly / Yearly pivots
Dynamic line extension
Labels with prices
Custom colours
Only draws selected pivot levels
Efficient matrix-based pivot system
💎 TECHNICAL EXCELLENCE
✔ Pine Script v6
✔ Efficient arrays & memory handling
✔ Clean dynamic updates
✔ Max-performance structure
✔ Modular design (each component can be toggled)
✔ Integrates all ICT concepts in one tool
🎯 Who Is This Indicator For?
Perfect for:
ICT Traders
Smart Money / Institutional Traders
Day Traders & Scalpers
Swing Traders using OB/FVG
Liquidity hunters
Market structure based traders
Volume-spread or PVSRA focused traders
This combines multiple institutional concepts without cluttering the chart.
🏆 Final Notes
This is a true all-in-one institutional suite, replacing up to 8 separate indicators.
Designed for precision, clarity, and professional price-action workflow.
FXGringo1.2FXGringo - Decision Points
This indicator identifies support and resistance zones based on reference points provided in the levels field, interpreting them as potential areas of price reaction. From these points, the script plots strength levels, allowing the trader to visualize regions where the price may encounter natural barriers to equilibrium between supply and demand.
Although the internal calculations do not directly reveal the complete methodology, its logic can be compared to concepts similar to gamma levels (GEX), insofar as it seeks to map zones where price movement tends to be more sensitive due to the concentration of positions or relevant market flows.
How the Indicator Works:
Input of External Points:
The user manually provides price points that represent potential support or resistance levels.
Strength Classification:
The indicator processes these points and plots each level based on criteria such as distance from the current price, frequency of occurrence in the history, and pre-calculated volatility variation. This generates a visual and quantitative hierarchy among the provided levels.
Context Analysis:
Based on the interaction between price and these levels, the script identifies and plots zones of greater relevance—where the price tends to react, consolidate, or reverse.
Confluence Analysis:
Observe how the external levels align with peaks, troughs, and volume zones. The overlap of strong levels often indicates areas of great institutional interest.
Risk Management:
Use the identified levels to plan entry and exit points and stop-loss or take-profit placement, based on the relative strength of the levels.
Modern Conceptual Basis: The methodology, although proprietary, can be compared to how gamma levels reflect zones of greater price sensitivity relative to the market's aggregate exposure.
Conclusion:
This indicator acts as an advanced tool for interpreting support and resistance levels, using external data to build a dynamic map of market interest zones. Its operation can be seen as an analogy to gamma levels (GEX), identifying regions where the price tends to react more significantly due to liquidity concentration or position imbalance. This approach provides the trader with a refined view of the areas of influence of large players, assisting in making decisions with greater precision and confidence.
Force DashboardScalping Dashboard - Complete User Guide
Overview
This scalping system consists of two complementary TradingView indicators designed for intraday trading with no overnight holds:
Force Dashboard - Single-row table showing real-time market bias and entry signals
Large Order Detection - Visual diamonds showing institutional order flow
Together, they provide a complete at-a-glance view of market conditions optimized for quick entries and exits.
Recommended Timeframes
Primary Scalping Timeframes
1-minute chart: Ultra-fast scalps (30 seconds - 3 minutes hold time)
2-minute chart: Quick scalps (2-5 minutes hold time)
5-minute chart: Standard scalps (5-15 minutes hold time)
Best Practices
Use 1-2 minute for highly liquid instruments (ES, NQ, major forex pairs)
Use 5-minute for less liquid markets or if you prefer fewer signals
Never hold past the last hour of trading to avoid overnight risk
Set hard stop times (e.g., exit all positions by 3:45 PM EST)
Dashboard Components Explained
Core Indicators (Circles ●)
MACD (5/13/5)
Green ● = Bullish momentum (MACD histogram positive)
Red ● = Bearish momentum (MACD histogram negative)
Gray ● = No clear momentum
Use: Confirms trend direction and momentum shifts
EMA (9/20/50)
Green ● = Price > EMA9 > EMA20 (uptrend)
Red ● = Price < EMA9 < EMA20 (downtrend)
Gray ● = Choppy/sideways
Use: Identifies the immediate micro-trend
Stoch (5-period Stochastic)
Green ● = Oversold (<20) - potential reversal up
Red ● = Overbought (>80) - potential reversal down
Gray ● = Neutral zone (20-80)
Use: Spots reversal opportunities at extremes
RSI (7-period)
Green ● = Oversold (<30)
Red ● = Overbought (>70)
Gray ● = Neutral
Use: Confirms overbought/oversold conditions
CVD (Cumulative Volume Delta)
Green ● = CVD above its moving average (buying pressure)
Red ● = CVD below its moving average (selling pressure)
Gray ● = Neutral
Use: Shows overall buying vs selling pressure
ΔCVD (Delta CVD - Rate of Change)
Green ● = CVD accelerating upward (buying acceleration)
Red ● = CVD accelerating downward (selling acceleration)
Gray ● = No acceleration
Use: Detects momentum shifts in order flow
Imbal (Order Flow Imbalance)
Green ● = Buy pressure >2x sell pressure
Red ● = Sell pressure >2x buy pressure
Gray ● = Balanced
Use: Identifies extreme one-sided order flow
Vol (Volume Strength)
Green ● = Volume >1.5x average (strong interest)
Red ● = Volume <0.7x average (low interest)
Gray ● = Normal volume
Yellow background = Volume surge (>2x average) - BIG MOVE ALERT
Use: Confirms conviction behind price moves
Tape (Tape Speed)
Green ● = Fast order flow (>1.3x normal)
Red ● = Slow order flow (<0.7x normal)
Gray ● = Normal speed
Yellow background = Very fast tape (>1.5x) - RAPID EXECUTION ALERT
Use: Measures urgency and speed of orders
Key Levels
Support (Supp)
Shows the nearest high-volume support level below current price
Bright Green background = Price is AT support (within 0.3%) - BOUNCE ZONE
Green background = Price above support (healthy)
Red background = Price below support (broken support, now resistance)
Resistance (Res)
Shows the nearest high-volume resistance level above current price
Bright Orange background = Price is AT resistance (within 0.3%) - REJECTION ZONE
Red background = Price below resistance (facing overhead supply)
Green background = Price above resistance (breakout)
These levels update automatically every 3 bars based on volume profile
Entry Signal Components
Score
Displays format: "6L" (6 long indicators) or "4S" (4 short indicators)
Bright Green = 6-7 indicators aligned for long
Light Green = 5 indicators aligned for long
Yellow = 4 indicators aligned (weaker setup)
Gray = No alignment
Red/Orange colors = Same scale for short setups
Score of 5+ indicates high-probability setup
SCALP (Main Entry Signal)
BRIGHT GREEN "LONG" = High-quality long scalp (Score 5+)
Green "LONG" = Decent long scalp (Score 4)
BRIGHT ORANGE "SHORT" = High-quality short scalp (Score 5+)
Red "SHORT" = Decent short scalp (Score 4)
Gray "WAIT" = No clear setup - STAY OUT
Entry Strategies
Strategy 1: High-Probability Scalps (Conservative)
When to Enter:
SCALP column shows BRIGHT GREEN "LONG" or BRIGHT ORANGE "SHORT"
Score is 5 or higher
Vol or Tape has yellow background (volume surge)
Example Long Setup:
SCALP = BRIGHT GREEN "LONG"
Score = 6L
Vol = Yellow background
Price AT Support (bright green Supp cell)
EMA, MACD, CVD, ΔCVD, Imbal all green
Entry: Enter immediately on next candle
Target: 0.5-1% move or resistance level
Stop: Below support or -0.3%
Hold Time: 2-10 minutes
Strategy 2: Momentum Scalps (Aggressive)
When to Enter:
Tape has yellow background (fast tape)
Vol has yellow background (volume surge)
ΔCVD is green (for longs) or red (for shorts)
Imbal shows strong imbalance in your direction
Score is 4+
Example Short Setup:
Tape & Vol = Yellow backgrounds
ΔCVD = Red, Imbal = Red
Price AT Resistance (bright orange)
Score = 5S
Entry: Enter immediately
Target: Quick 0.3-0.7% move
Stop: Tight -0.2%
Hold Time: 1-5 minutes
Strategy 3: Reversal Scalps (Mean Reversion)
When to Enter:
Stoch shows oversold (green) or overbought (red)
RSI confirms the extreme
Price is AT Support (for longs) or AT Resistance (for shorts)
ΔCVD and Imbal start reversing direction
Score is 4+
Example Long Setup:
Stoch = Green (oversold)
RSI = Green (oversold)
Supp = Bright green (at support)
ΔCVD turns green
Imbal turns green
Score = 4L or 5L
Entry: Wait for confirmation candle
Target: Move back to EMA9 or mid-range
Stop: Below the low
Hold Time: 3-8 minutes
Large Order Detection Usage
Diamond Signals
Green diamonds below bar = Large buy orders (institutional buying)
Red diamonds above bar = Large sell orders (institutional selling)
Size matters: Larger diamonds = larger order flow
How to Use with Dashboard
Confirmation Entries
Dashboard shows "LONG" signal
Green diamond appears
Enter immediately - institutions are buying
Divergence Alerts (CAUTION)
Dashboard shows "LONG" signal
RED diamond appears (institutions selling)
DO NOT ENTER - conflicting order flow
Cluster Patterns
Multiple green diamonds in row = Strong accumulation, stay long
Multiple red diamonds in row = Strong distribution, stay short
Alternating colors = Chop, avoid trading
Risk Management Rules
Position Sizing
Risk 0.5-1% of account per scalp
Maximum 3 concurrent positions
Reduce size after 2 consecutive losses
Stop Loss Guidelines
Tight stops: 0.2-0.3% for 1-2 min charts
Standard stops: 0.3-0.5% for 5 min charts
Always use stop loss - no exceptions
Place stops below support (longs) or above resistance (shorts)
Take Profit Targets
Target 1: 0.3-0.5% (take 50% off)
Target 2: 0.7-1% (take remaining 50%)
Move stop to breakeven after Target 1 hit
Trail stop if Score remains high
Time-Based Exits
Exit immediately if:
SCALP changes from LONG/SHORT to WAIT
Score drops below 3
Large diamond appears in opposite direction
Maximum hold time: 15 minutes (even if profitable)
Hard exit time: 30 minutes before market close
Trading Sessions
Best Times to Scalp
High-Liquidity Sessions
9:30-11:00 AM EST (Market open, highest volume)
2:00-3:30 PM EST (Afternoon session, good moves)
Avoid
11:30 AM-1:30 PM EST (Lunch, low volume)
Last 30 minutes (unpredictable, don't initiate new trades)
News releases (wait 5 minutes for volatility to settle)
Common Patterns & Setups
The Perfect Storm (Highest Probability)
Score = 6L or 7L
SCALP = BRIGHT GREEN
Vol + Tape = Yellow backgrounds
Green diamond appears
Price AT Support
Win rate: ~70-80%
The Fade Setup (Counter-Trend)
Price hits resistance (bright orange)
Stoch + RSI overbought (red)
Red diamond appears
CVD starts turning red
SCALP shows "SHORT"
Win rate: ~60-70%
The Breakout Continuation
Price breaks resistance (Res turns green)
EMA, MACD green
Vol surge (yellow)
Multiple green diamonds
SCALP = "LONG"
Win rate: ~65-75%
Warning Signs - DO NOT TRADE
Red Flags
❌ SCALP shows "WAIT"
❌ Score below 3
❌ Vol and Tape both gray (no volume)
❌ Conflicting signals (dashboard says LONG but red diamonds appearing)
❌ Alternating green/red circles (choppy market)
❌ Support and Resistance very close together (tight range)
Market Conditions to Avoid
Low volume periods
Major news releases (first 5 minutes after)
First 2 minutes after market open
Wide spreads
Consecutive losing trades (take a break after 2 losses)
Quick Reference Checklist
Before Taking ANY Trade:
☑ SCALP shows LONG or SHORT (not WAIT)
☑ Score is 4 or higher
☑ Vol or Tape shows activity
☑ No conflicting diamond signals
☑ Stop loss level identified
☑ Target profit level identified
☑ Not in restricted time periods
After Entering:
☑ Set stop loss immediately
☑ Set profit targets
☑ Watch SCALP column - exit if changes to WAIT
☑ Watch for opposite-colored diamonds
☑ Move stop to breakeven after first target
☑ Exit all by market close
Advanced Tips
Scalping Psychology
Be patient: Wait for Score 5+ setups
Be decisive: When signal appears, act immediately
Be disciplined: Follow your stop loss always
Be flexible: Exit quickly if dashboard reverses
Optimization
Backtest on your specific instrument
Adjust RSI/Stoch levels for your market
Fine-tune volume thresholds
Keep a trade journal to track which setups work best
Multi-Timeframe Confirmation
Use 5-min dashboard as "trend filter"
Take 1-min trades only in direction of 5-min SCALP signal
Increases win rate by ~10-15%
Troubleshooting
Q: Dashboard shows WAIT most of the time
Normal - scalping is about patience. Quality > Quantity
3-8 good setups per day is excellent
Q: Too many false signals
Increase minimum Score requirement to 5 or 6
Only trade with volume surge (yellow backgrounds)
Add large order detection confirmation
Q: Signals too slow
You may be on too high a timeframe
Try 1-minute chart for faster signals
Ensure real-time data feed is active
Q: Support/Resistance not updating
Normal - updates every 3 bars
If completely stuck, remove and re-add indicator
Summary
This scalping system works best when:
✅ Multiple indicators align (Score 5+)
✅ Volume and tape speed confirm the move
✅ Order flow (diamonds) confirms direction
✅ Price is at key levels (support/resistance)
✅ You manage risk strictly
✅ You exit before market close
The golden rule: When SCALP says WAIT, you WAIT. Discipline beats frequency.
ob-fvg-jorgechutofx📊 **4-Candle Pattern (OB + FVG + BOS)**
This indicator identifies a four-candle structural pattern combining **Order Block (OB)**, **Fair Value Gap (FVG)**, and **Break of Structure (BOS)**.
* **Candle 1:** reference level to be broken.
* **Candle 2:** potential **Order Block** (origin zone).
* **Candle 3:** confirms the **structure break**.
* **Candle 4:** forms the **FVG**, showing market imbalance.
Perfect for spotting **institutional entry zones** and validating **market inefficiencies** across any timeframe.
Adaptive AI Polar Oscillator [by Oberlunar]Adaptive AI Oscillator blends trading signals with two order-flow style oscillators and a lightweight online-learning model to keep it reactive, adaptive and computationally feasible.
What it is
A lightweight Multi Layer Perceptron (neural net) updates online on every bar, so it keeps adapting as conditions change.
An adaptive collector that fuses features like Price (close, ohlc4, etc...), a selectable (but not used in the original implementation) Moving Average (EMA/SMA/WMA/RMA/HMA/DEMA/TEMA), RSI, the classic volume datafeeds, plus two “OberPolar” oscillators computed above and below the current integral area price.
What you see
White line — the model’s denormalised forecast (in price units).
Colored price line — actual price, shown aqua when forecast ≥ price (“golden” bias) and red when forecast < price (“death” bias).
Why it helps
Combines heterogeneous information (trend, momentum, participation, regional buy/sell pressure) into a single adaptive forecast.
Online learning reduces regime staleness versus fixed-parameter indicators.
The aqua/red bias offers a quick, visual state for discretionary decisions.
How it works (intuitive)
Each AI input is standardised (z-score) with optional clamping to mitigate outliers.
A rolling window of recent values feeds a 2-layer AI to predict one step ahead.
After each bar closes, the model compares forecast vs. reality and nudges its weights (SGD with momentum, L2, optional gradient clipping).
The forecast is de-standardised back to price units and plotted as the white line.
Reading guide
Crossovers between forecast and price often mark potential bias flips.
Persistent aqua → model perceives supportive/positive conditions.
Persistent red → model perceives headwinds/negative conditions.
Complex Strategy — Oscillator Trendline Break
Connect the first pivot in the fading bias with the first pivot in the new bias, then trade the break of that line in the direction of the new bias.
Idea in one line
Use the Adaptive AI Oscillator (green = bullish bias, red = bearish). When bias flips, build a line across the oscillator pivots that “span” the transition; the break of that line times the entry.
Long setup (mirror for shorts)
Bias transition : a bearish (red) regime is ongoing, then the oscillator turns bullish (green).
Anchor pivots : take the first MIN in red just before/around the flip and the first MAX in green after the flip. Draw a trendline L through these two oscillator values (time–value line).
Trigger : enter LONG on the close that breaks above L —optional confirmations: price above your MA, non-decreasing volume, no immediate supply zone overhead.
Risk : stop below the last oscillator swing low or below a retest of L; first target at 1R–1.5R or at the opposite bias zone; trail under successive oscillator higher lows.
Short setup
Bias turns from green (bullish) to red (bearish).
Connect the first MAX in green to the first MIN in red → line L.
Enter SHORT on a close below L ; stop above the last oscillator swing high; symmetric targets/trailing.
Complex Strategy #2 — Bias-Pivot Breakout with Exit on Line Failure
Connect two pivots of the same bias to build a dynamic barrier; trade the breakout in the bias direction and exit when that line later fails.
Long play (mirror for shorts)
Build the line. During a green (bullish) phase, mark the first two local MAX of the oscillator. Connect them to form the yellow resistance line L (extend it right). If a new, clearer MAX appears before a break, re-anchor using the two most recent highs.
Entry trigger. Go LONG on a close above L (the “Break and LONG” in the image). Optional filters: price above your MA, rising volume, no immediate overhead level.
Risk. Initial stop: below the last oscillator swing low or below the retest of L . Position size for 1–2R baseline.
Exit. Close the long when the oscillator later breaks back below L (the “Break and LONG exit”), or on a bias flip to red, or at a fixed target/trailing under higher lows.
Short play (symmetric)
In a red phase, connect the first two local MIN to form support line L .
Enter SHORT on a close below L ; stop above the last oscillator swing high; exit on a break back above L or on a flip to green.
Notes
Require a minimum slope/spacing between pivots to avoid flat/noisy lines.
Re-anchor the line if fresher pivots emerge before a valid break.
Use with your regime filter (MA slope, higher-timeframe bias) to reduce whipsaws.
Complex Strategy #3 — Lateral Box & Zero-Slope Breakout
An easy way to understand sideways phases and the next price direction: draw two zero-slope lines (flat upper/lower bounds) across the oscillator’s lateral area; when a strong break occurs, trade in the direction of that break.
How to use it
Identify a lateral area on the oscillator (flat, low-variance region). Place a flat upper line on tops and a flat lower line on bottoms (slope ≈ 0).
Wait for a decisive break : close outside the band with expansion (range/true range rising, or a wide candle).
• Break up → bias for LONG .
• Break down → bias for SHORT .
Why it helps
Flat lines isolate congestion; the next impulsive move is often revealed by which side is broken with force.
It filters noise inside the range and focuses attention on the transition from balance → imbalance.
Practical filters (optional)
Require minimum bar body/ATR on the breakout candle to avoid false breaks .
Confirm with your regime filter (e.g., price above/below your MA) or a quick retest that holds.
Invalidate the signal if the price immediately returns inside the band on the next bar.
General Operational notes
If new pivots form before a break, re-anchor the line with the most recent qualifying pair (keeps the structure fresh).
Ignore very shallow lines (near-flat): require a minimum slope or angle to avoid noise.
Combine with your bias filter (e.g., MA slope/regime) to reduce false starts.
Limits & good practice
Adaptive models can react to noise; treat signals as context within a risk-managed plan.
No model predicts the future—this summarises evolving conditions compactly.
— Oberlunar 👁 ★
