Average True Range PercentWhen writing the Quickfingers Luc base scanner (Marvin) script, I wanted a measure of volatility that would be comparable between charts. The traditional Average True Range (ATR) indicator calculates a discrete number providing the average true range of that chart for a specified number of periods. The ATR is not comparable across different price charts.
Average True Range Percent (ATRP) measures the true range for the period, converts it to a percentage using the average of the period's range ((high + low) / 2) and then smooths the percentage. The ATRP provides a measure of volatility that is comparable between charts showing their relative volatility.
Enjoy.
Cari skrip untuk "grid"
Up & Down Trend Trading Strategy - BNB/USDT 15minThis strategy will focus on up trend trading and down trend trading based on several indicators such as;
for up trend
1. SAR indicator
2. Super trend indicator
3. Simple moving average for the period of 100
down trend
1. RSI Indicator
2. Money flow index
3. Relative volatility index
4. Balance of powder
VWAP CATS background flipped 4.0VWAP CATS Background Flipped 4.0 is a sophisticated Pine Script v5 indicator for TradingView that combines a configurable moving average (MA) with dynamic Gann Square of 9 levels to create a multi-layered background shading system for price action analysis. It visualizes support/resistance zones around a central MA (often VWAP or RVWAP) using incremental offsets (either % or absolute points), generating symmetrical bands that resemble a "CATS" (Concentric Adaptive Tiered System) — hence the name.The background is "flipped" in the sense that shading intensity and structure emphasize higher-tier zones, and labels are placed to the right of the chart for future projection.Key FeaturesFeature
Description
Multi-MA Engine
Supports 20+ MA types: EMA, DEMA, TEMA, SMA, VWAP, RVWAP, HMA, ALMA, custom volume blends (CVB1–4)
RVWAP Mode
Rolling VWAP with adaptive or fixed time window (days/hours/minutes)
Gann Square of 9 Logic
Generates 80+ symmetric levels (0.25x to 17x increment) above/below the MA
Dual Increment Mode
Choose Percent or Points for spacing
Background Fills
Tiered transparency fills between Gann levels (darker = stronger zones)
Visual MA Offset
Shift MA line left/right without breaking fill alignment
Smart Labels
Projected labels on last bar: "FV", "normal", "high", "3/4" at key levels
Performance Optimized
Hidden plots + label cleanup to prevent lag
Primary Use Cases
1. Institutional VWAP Anchoring
Use RVWAP (1-day fixed) as maRaw
Set Increment = 0.5 points or 0.05%
Watch price interaction with "normal" (2x), "high" (4x), "3/4" (6x) zones
Ideal for intraday scalping on indices (ES, NQ) or forex
2. Swing Trading with Gann Projections
Use 400-period SMA/EMA on daily chart
Increment in Percent mode (~1.22%)
Identify confluence when price rejects at 2x, 4x, or 6x bands
Labels project future targets to the right
3. Volume-Weighted Mean Reversion
Select CVB1–CVB4 for heavy volume smoothing
Use Points mode for stocks with stable tick sizes (e.g. $0.50 increments)
Trade mean reversion between ±1x and ±2x bands
4. Risk Management & Stop Placement
Place stops beyond 2x or 4x bands
Take profits at next major tier (e.g. 4x → 6x)
Pro Tips
Enable "Use Fixed Time Period" for RVWAP to avoid session reset issues
Increase i_label_offset on lower timeframes to avoid overlap
Combine with volume profile or order flow for confluence
The "FV" label marks the Fair Value MA — core anchor
Summary"VWAP CATS Background Flipped 4.0" turns any moving average into a dynamic Gann-based pricing grid with intelligent background shading and forward-projected labels — perfect for institutional-style mean reversion, swing targeting, and risk-defined trading."
Holographic Market Microstructure | AlphaNattHolographic Market Microstructure | AlphaNatt
A multidimensional, holographically-rendered framework designed to expose the invisible forces shaping every candle — liquidity voids, smart money footprints, order flow imbalances, and structural evolution — in real time.
---
📘 Overview
The Holographic Market Microstructure (HMS) is not a traditional indicator. It’s a visual architecture built to interpret the true anatomy of the market — a living data structure that fuses price, volume, and liquidity into one coherent holographic layer.
Instead of reacting to candles, HMS visualizes the market’s underlying micro-dynamics : where liquidity hides, where volume flows, and how structure morphs as smart money accumulates or distributes.
Designed for system-based traders, volume analysts, and liquidity theorists who demand to see the unseen — the invisible grid driving every price movement.
---
🔬 Core Analytical Modules
Microstructure Analysis
Deconstructs each bar’s internal composition to identify imbalance between aggressive buying and selling. Using a configurable Imbalance Ratio and Liquidity Threshold , the algorithm marks low-liquidity zones and price inefficiencies as “liquidity voids.”
• Detects hidden supply/demand gaps.
• Quantifies micro-level absorption and exhaustion.
• Reveals flow compression and expansion phases.
Smart Money Tracking
Applies advanced volume-rate-of-change and price momentum relationships to map institutional activity.
• Accumulation Zones – Where price rises on expanding volume.
• Distribution Zones – Where price declines on rising volume.
• Automatically visualized as glowing boxes, layered through time to simulate footprint persistence.
Fractal Structure Mapping
Reveals the recursive nature of price formation. HMS detects fractal highs/lows, then connects them into an evolving structure.
• Defines nested market structure across multiple scales.
• Maps trend progression and transition points.
• Renders with adaptive glow lines to reflect depth and strength.
Volume Heat Map
Transforms historical volume data into a 3D holographic heat projection.
• Each band represents a volume-weighted price level.
• Gradient brightness = relative participation intensity.
• Helps identify volume nodes, voids, and liquidity corridors.
HUD Display System
Real-time analytical dashboard summarizing the system’s internal metrics directly on the chart.
• Flow, Structure, Smart$, Liquidity, and Divergence — all live.
• Designed for both scalpers and swing traders to assess micro-context instantly.
---
🧠 Smart Money Intelligence Layer
The Smart Money Index dynamically evaluates the harmony (or conflict) between price momentum and volume acceleration. When institutions accumulate or distribute discreetly, volume surges ahead of price. HMS detects this divergence and overlays it as glowing smart money zones.
◈ ACCUM → Institutional absorption, early uptrend formation.
◈ DISTRIB → Distribution and top-heavy conditions.
○ IDLE → Neutral flow equilibrium.
Divergences between price and volume are signaled using holographic alerts ( ⚠ ALERT ) to highlight exhaustion or trap conditions — often precursors to structural reversals.
---
🌀 Fractal Market Structure Engine
The fractal subsystem recursively identifies local pivot symmetry, connecting micro-structural highs and lows into a holographic skeleton.
• Bullish Structure — Higher highs & higher lows align (▲ BULLISH).
• Bearish Structure — Lower highs & lower lows dominate (▼ BEARISH).
• Ranging — Fractal symmetry balance (◆ RANGING).
Each transition is visually represented through adaptive glow intensity, producing a living contour of market evolution .
---
🔥 Volume Heat Map Projection
The heatmap acts as a volumetric X-ray of the recent 100–300 bars. Each horizontal segment reflects liquidity density, rendered with gradient opacity from cold (inactive) to hot (highly active).
• Detects hidden accumulation shelves and distribution ridges.
• Identifies imbalanced liquidity corridors (voids).
• Reveals the invisible scaffolding of the order book.
When combined with smart money zones and structure lines, it creates a multi-layered holographic perspective — allowing traders to see liquidity clusters and their interaction with evolving structure in real time.
---
💎 Holographic Visual Engine
Every element of HMS is dynamically color-mapped to its visual theme . Each theme carries a distinct personality:
Aeon — Neon blue plasma aesthetic; futuristic and fluid.
Cyber — High-contrast digital energy; circuit-like clarity.
Quantum — Deep space gradients; reflective of non-linear flow.
Neural — Organic transitions; biological intelligence simulation.
Plasma — Vapor-bright gradients; high-energy reactive feedback.
Crystal — Minimalist, transparent geometry; pristine data visibility.
Optional Glow Effects and Pulse Animations create a living hologram that responds to real-time market conditions.
---
🧭 HUD Analytics Table
A live data matrix placed anywhere on-screen (top, middle, or side). It summarizes five critical systems:
Flow: Order flow bias — ▲ BUYING / ▼ SELLING / ◆ NEUTRAL.
Struct: Microstructure direction — ▲ BULLISH / ▼ BEARISH / ◆ RANGING.
Smart$: Institutional behavior — ◈ ACCUM / ◈ DISTRIB / ○ IDLE.
Liquid: Market efficiency — ⚡ VOID / ● NORMAL.
Diverg: Price/Volume correlation — ⚠ ALERT / ✓ CLEAR.
Each metric’s color dynamically adjusts according to live readings, effectively serving as a neural HUD layer for rapid interpretation.
---
🚨 Alert Conditions
Stay informed in real time with built-in alerts that trigger under specific structural or liquidity conditions.
Liquidity Void Detected — Market inefficiency or thin volume region identified.
Strong Order Flow Detected — Aggressive buying or selling momentum shift.
Smart Money Activity — Institutional accumulation or distribution underway.
Price/Volume Divergence — Volume fails to confirm price trend.
Market Structure Shift — Fractal structure flips directional bias.
---
⚙️ Customization Parameters
Adjustable Microstructure Depth (20–200 bars).
Configurable Imbalance Ratio and Liquidity Threshold .
Adaptive Smart Money Sensitivity via Accumulation Threshold (%).
Multiple Fractal Depth Layers for precise structural analysis.
Scalable Heatmap Resolution (5–20 levels) and opacity control.
Selectable HUD Position to suit personal layout preferences.
Each parameter adjusts the balance between visual clarity and data density , ensuring optimal performance across intraday and macro timeframes alike.
---
🧩 Trading Application
Identify early signs of institutional activity before breakouts.
Track structure transitions with fractal precision.
Locate hidden liquidity voids and high-value areas.
Confirm strength of trends using order-flow bias.
Detect volume-based divergences that often precede reversals.
HMS is designed not just for observation — but for contextual understanding . Its purpose is to help traders anchor strategies in liquidity and flow dynamics rather than surface-level price action.
---
🪞 Philosophy
Markets are holographic. Each candle contains a reflection of every other candle — a fractal within a fractal, a structure within a structure. The HMS is built to reveal that reflection, allowing traders to see through the market’s multidimensional fabric.
---
Developed by: AlphaNatt
Version: v6
Category: Market Microstructure | Volume Intelligence
Framework: PineScript v6 | Holographic Visualization System
Not financial advice
0DTE Options - Iron Condor & ButterflyTo help options traders:
Plan and structure Iron Condor or Butterfly spreads in “Setup Mode.”
Track live trades, including P&L, breach risk, and strike distances, in “Live Mode.”
Visualize the trade on the price chart with profit zones, breakeven lines, strike markers, and alerts.
Evaluate market conditions using IV Rank, ATR-based range modeling, and modeled Delta approximation.
Essentially, it turns your TradingView chart into an options risk graph + planning terminal.
⚙️ Core Modes of Operation
🧱 1. Setup Mode
Used for planning new trades. It automatically suggests strikes based on:
ATR (volatility proxy)
IV Rank
Target Delta
Chosen risk tier (High / Mid / Low / Delta)
You can:
Preview recommended short and long strikes.
See estimated credit, width, and risk/reward ratios in a setup table.
Auto-feed these calculated strikes into the Live Mode to track them later.
Example Use:
Before market open, choose Setup Mode → Mid Risk Tier → see what strike widths and credits make sense for the day.
📈 2. Live Mode
Used to track real trades you’ve already opened.
You can:
Paste your real trade data (strikes, credits, etc.) into the 📋 paste field.
Or auto-feed from Setup Mode (if “Auto-Feed” is enabled).
The indicator then plots:
Short/long strikes
Breakevens
Profit/loss zone
Real-time breach detection and delta drift
Alerts when price nears your strikes or exits your safe zone.
Example Use:
After opening an Iron Condor on SPX, paste in 626,628,620,618,1.20,1, and the chart visually shows your safe range and warning zones.
🧮 Built-In Calculations
1. IV Rank (Volatility Environment)
Uses a 20-day log return volatility model to calculate IV Rank (percentile of volatility over the last 252 bars).
You can use this automatically or manually override it if you have data from your broker.
→ High IV Rank (>50) = better for selling Iron Condors (more premium).
2. ATR (Average True Range)
Measures short-term volatility to estimate expected daily price movement.
Used in Setup Mode to model distance between strikes.
3. Strike Calculations (Setup Mode)
Based on risk tier:
High Risk → wide wings, high credit, high potential drawdown
Mid Risk → balanced setup
Low Risk → narrow wings, safer but less credit
Delta Mode → based purely on target delta (e.g., 0.20)
Uses ATR × multiplier to determine how far short strikes should be from current price.
4. Credit Estimation
Based on strike width × IV Rank multiplier:
IV > 50 → 30% of width
IV 30–50 → 25%
IV < 30 → 20%
5. Profit & Loss Modeling
The indicator computes:
Max Profit:
Iron Condor → credit × 100 × contracts
Butterfly → (wing width − debit) × 100 × contracts
Max Loss:
Iron Condor → width − credit
Butterfly → debit × 100 × contracts
Breakevens:
Iron Condor → short strikes ± credit
Butterfly → body ± debit
Current P&L: Approximated by where the underlying is relative to the short/long strikes.
6. Delta Modeling
Estimates each short strike’s modeled delta based on how far it is from current price.
Displays total delta balance to show directional bias.
If Delta drifts too high → market imbalance → consider rolling or adjusting.
7. Breach Detection System
Automatically classifies your trade as:
🟢 In Range: Price between short strikes (safe zone).
🟠 Near Breach: Price close to short strike (risk zone).
🔴 Breached: Price outside long strike (stop or adjust zone).
This dynamically changes color in your profit box and info label.
🎨 Visual Components
Element Meaning Color
Red Line Put side strikes 🔻 Red
Green Line Call side strikes 🔺 Green
Yellow Dotted Lines Breakevens 🟡 Yellow
Green Box Profit zone 🟩 Light green
Orange Box Adjustment zone (near breach) 🟧 Orange
Red Box Breach zone 🟥 Red
White Line Current price ⚪ White
Optional labels display strike details and distances (e.g., “📉 Short Put: 620 – 5 pts away”).
📊 Setup Table (Setup Mode Only)
Displays a grid comparing all risk tiers:
Tier Short Call Short Put Width Est. Credit R:R
High 632 614 4.0 $1.20 0.43
Mid 630 616 3.0 $0.90 0.43
Low 628 618 2.0 $0.60 0.43
Highlighted row = selected risk tier.
This lets you compare how wide/narrow each setup is before committing to a trade.
🧾 Info Box (Live Mode)
Displays real-time stats such as:
🔶 IRON CONDOR | 1 Contract
📊 Calls: 626 / 628 | Puts: 620 / 618
💵 Credit: $1.20 | 💰 Profit: $120 | 🔴 Loss: $180
⬆️ BE: 627.2 | ⬇️ BE: 618.8
📍 Current: $623 | 💵 P&L: +$35.00 (+29.1%)
📏 To Short Call: 3 | To Short Put: 3
📊 Delta: 0.05 | IV Rank: 56% (FAVORABLE)
🔴 BREACH STATUS: In Range
🚨 Alerts
The indicator generates TradingView alerts for:
⚠️ Approaching Call Zone → nearing short call
⚠️ Approaching Put Zone → nearing short put
🛑 Stop Loss Triggered → current P&L exceeds loss threshold
🟠 Near Breach → price entering adjustment zone
🔴 Breached → price outside protection (long strikes)
These alerts can be used with TradingView notifications or webhooks.
🧠 How to Use It Step-by-Step
A. Planning (Setup Mode)
Set mode to “Setup.”
Adjust:
Risk Tier (High / Mid / Low / Delta)
Target Delta (0.15–0.30 recommended)
Strike Interval (e.g., 1.0 or 5.0)
Check Setup Table → see suggested strikes & credits.
Optionally toggle Auto-Feed → Live to send to live mode later.
B. Executing (Broker)
Confirm and enter your trade in your brokerage (use the strikes shown).
Record your strikes, net credit/debit, and number of contracts.
C. Tracking (Live Mode)
Switch to “Live” mode.
Paste your strikes in the 📋 Paste Data field:
Iron Condor Example: 626,628,620,618,1.20,1
Butterfly Example: 600,620,640,2.50,2
The chart updates:
Lines = your strikes
Boxes = profit/risk zones
Labels = strike info, distance to price
Info box = P&L, delta, IV rank, breach status
Set alerts for automatic notifications.
D. Managing the Trade
When the chart turns orange or red, you’re approaching or breaching a strike.
Use this signal to roll, hedge, or close your trade.
Monitor Gamma Risk: warning appears when price nears short strikes (explosive delta risk).
📌 Summary
Feature Description
Mode Switching Plan (Setup) or Track (Live)
IV Rank & ATR Modeling Estimates volatility environment
Auto Strike Planning Suggests strikes based on risk/delta
Visual Range Map Profit, breakeven, and adjustment zones
Real-Time Alerts Warns when nearing or breaching strikes
Trade Info Box Displays live risk, reward, delta, IV, and P&L
Setup Table Compares setups across risk tiers
Fully Configurable Works for Iron Condors or Butterflies
BlackScrum Swing Boxes 1/2/3 After seeing influencers selling their indicator suite's online, I decided to start making replicas of them, maybe mine are better, maybe they are worse. I use them in my day to day trading and they help me make money, hopefully they help you make money.
Not financial advice, Do Your Own Research.
Everything provided without warranty or liability. If you stuff up, learn from it, get better, we all make mistakes.
// BlackScrum — 1/2/3-Bar Swing Boxes (auto timeframe)
//
// DESCRIPTION
// This indicator displays three swing-direction boxes (1B, 2B, 3B) in the top-right corner of the chart.
// The boxes automatically adapt to the chart's timeframe (15m, 1H, 4H, 1D, etc.).
// Each box represents the direction of the most recently confirmed swing pivot:
// • 1B → 1-bar swing (fastest, most sensitive)
// • 2B → 2-bar swing (medium confirmation)
// • 3B → 3-bar swing (slowest, strongest confirmation)
//
// COLORS
// • GREEN = last confirmed swing pivot was a higher low (up swing)
// • RED = last confirmed swing pivot was a lower high (down swing)
// • GREY = no clear swing yet (fresh/transition area)
//
// CONFLUENCE
// • ALL GREEN = bullish alignment across 1B, 2B, 3B → strong trend continuation signal
// • ALL RED = bearish alignment across all three → strong downtrend continuation signal
//
// HOW TO USE (TRADEPLAY)
//
// 1) ENTRIES
// • Aggressive entry → enter when ALL GREEN prints on your timeframe.
// • Safer pullback entry → wait for 1B to briefly turn red during a green 2B/3B,
// then flip back to green. Enter on the re-flip.
// • Multi-timeframe filter:
// Take longs only when higher TF (e.g., 1H/4H) boxes are at least neutral-to-green.
//
// 2) EXITS
// • Weakness exit → when 1B flips against your position while 2B is neutral/red.
// • Full exit → when ALL RED prints.
// • Time stop → if price hasn’t moved after several bars of your execution timeframe.
//
// 3) STOP-LOSS / RISK
// • Place stops beyond the latest opposite swing used by 2B or 3B.
// • Add 0.5–1× ATR buffer if your market has stop-hunt volatility.
// • Always size position based on the distance to the swing stop.
//
// 4) WHEN TO IGNORE SIGNALS
// • Chop zones → 1B flipping repeatedly while 2B/3B disagree.
// • News candles → wait for pivots to confirm on the *closed* bar.
//
// 5) USING WITH OTHER TOOLS
// • With a trend ribbon (e.g., Larsson-style):
// Only take ALL GREEN longs when the ribbon is UP, and ALL RED shorts when ribbon is DOWN.
// • With a Fear & Greed index:
// Prefer longs when F&G > 60,
// Avoid longs when F&G < 40 unless countertrend scalping.
//
// 6) TIMEFRAME GUIDANCE
// • Scalping: 5m / 15m, confirmed by 1H or 4H boxes.
// • Swinging: 1H / 4H with daily filter.
// • Positioning: 1D with weekly confirmation.
//
// 7) INTERPRETATION CHEATSHEET
// • 1B green, 2B grey, 3B red → short-term bounce inside higher timeframe downtrend.
// • 1B/2B green, 3B grey → early trend reversal forming.
// • All grey → fresh swing area; wait for direction.
//
// 8) CUSTOMIZATION
// • len1 / len2 / len3 control sensitivity (higher = slower & cleaner).
// • Can add a timeframe header box (e.g., “15m / 4H / 1D”).
// • Can add a multi-timeframe grid (e.g., 15m | 1H | 4H | 1D each with 1B/2B/3B).
//
// ====================================================================================================
Moving Average Trend Strategy V2.1 — With Stop Loss and Add Posi**Strategy Feature Description:**
---
### **Entry Logic:**
* When **MA7** crosses **MA15**, and the distance between **MA15** and **MA99** is less than **0.5%**
* When **MA15** crosses **MA99**, and the distance between **MA7** and **MA15** is less than **0.5%**
* When the distance among all three MAs (**MA7**, **MA15**, **MA99**) is less than **0.5%** (adjustable via parameters)
---
### **Capital Management:**
* Initial capital: **$100**
* Each position uses **15%** of total capital
* Opens **both long and short positions simultaneously** (dual-direction mode)
---
### **Risk Control:**
* **Long position stop-loss:** Entry price − 2%
* **Short position stop-loss:** Entry price + 2%
* Uses a **five-level take-profit grid**:
* Every 5% profit → close 20% of position
* Any pending take-profit orders are automatically canceled when stop-loss triggers
---
### **Visualization Features:**
* Real-time display of the three moving averages
* Chart annotations for entry signal points
* All trade signals and performance can be viewed through **TradingView backtest reports**
---
### **Notes:**
* Parameters can be adjusted based on the volatility of the instrument (historical backtesting is recommended first)
* Dual-direction positions may generate **hedging costs** — recommended for low-fee markets
* Real trading must consider **exchange minimum order size limits**
* Suggest enabling a **volume filter mechanism** (extension interface already reserved)
* Always perform **historical backtesting and parameter optimization** in TradingView before connecting to live trading systems
US30 Quarter Levels (125-point grid) by FxMogul🟦 US30 Quarter Levels — Trade the Index Like the Banks
Discover the Dow’s hidden rhythm.
This indicator reveals the institutional quarter levels that govern US30 — spaced every 125 points, e.g. 45125, 45250, 45375, 45500, 45625, 45750, 45875, 46000, and so on.
These are the liquidity magnets and reaction zones where smart money executes — now visualized directly on your chart.
💼 Why You Need It
See institutional precision: The Dow respects 125-point cycles — this tool exposes them.
Catch reversals before retail sees them: Every impulse and retracement begins at one of these zones.
Build confluence instantly: Perfectly aligns with your FVGs, OBs, and session highs/lows.
Trade like a professional: Turn chaos into structure, and randomness into rhythm.
⚙️ Key Features
Automatically plots US30 quarter levels (…125 / …250 / …375 / …500 / …625 / …750 / …875 / …000).
Color-coded hierarchy:
🟨 xx000 / xx500 → major institutional levels
⚪ xx250 / xx750 → medium-impact levels
⚫ xx125 / xx375 / xx625 / xx875 → intraday liquidity pockets
Customizable window size, label spacing, and line extensions.
Works across all timeframes — from 1-minute scalps to 4-hour macro swings.
Optimized for clean visualization with no clutter.
🎯 How to Use It
Identify liquidity sweeps: Smart money hunts stops at these quarter zones.
Align structure: Combine with session opens, order blocks, or FVGs.
Set precision entries & exits: Trade reaction-to-reaction with tight risk.
Plan daily bias: Watch how New York respects these 125-point increments.
🧭 Designed For
Scalpers, day traders, and swing traders who understand that US30 doesn’t move randomly — it moves rhythmically.
Perfect for traders using ICT, SMC, or liquidity-based frameworks.
⚡ Creator’s Note
“Every 125 points, the Dow breathes. Every 1000, it shifts direction.
Once you see the rhythm, you’ll never unsee it.”
— FxMogul
ORDER BLCOK custom strategy# OB Matrix Strategy - Documentation
**Version:** 1.0
**Author:** HPotter
**Date:** 31/07/2017
The **OB Matrix Strategy** is based on the identification of **bullish and bearish Order Blocks** and the management of conditional orders with multiple Take Profit (TP) and Stop Loss (SL) levels. It uses trend filters, ATR, and percentage-based risk management.
---
## 1. Main Parameters
### Strategy
- `initial_capital`: 50
- `default_qty_type`: percentage of capital
- `default_qty_value`: 10
### Money Management
- `rr_threshold`: minimum Risk/Reward threshold to open a trade
- `risk_percent`: percentage of capital to risk per trade (default 2%)
- `maxPendingBars`: maximum number of bars for a pending order
- `maxBarsOpen`: maximum number of bars for an open position
- `qty_tp1`, `qty_tp2`, `qty_tp3`: quantity percentages for multiple TPs
---
## 2. Order Block Identification
### Order Block Parameters
- `obLookback`: number of bars to identify an Order Block
- `obmode`: method to calculate the block (`Full` or `Breadth`)
- `obmiti`: method to determine block mitigation (`Close`, `Wick`, `Avg`)
- `obMaxBlocks`: maximum number of Order Blocks displayed
### Main Variables
- `bullBlocks`: array of bullish blocks
- `bearBlocks`: array of bearish blocks
- `last_bull_volume`, `last_bear_volume`: volume of the last block
- `dom_block`: dominant block type (Bullish/Bearish/None)
- `block_strength`: block strength (normalized volume)
- `price_distance`: distance between current price and nearest block
---
## 3. Visual Parameters
- `Width`: line thickness for swing high/low
- `amountOfBoxes`: block grid segments
- `showBorder`: show block borders
- `borderWidth`: width of block borders
- `showVolume`: display volume inside blocks
- `volumePosition`: vertical position of volume text
Customizable colors:
- `obHighVolumeColor`, `obLowVolumeColor`, `obBearHighVolumeColor`, `obBearLowVolumeColor`
- `obBullBorderColor`, `obBearBorderColor`
- `obBullFillColor`, `obBearFillColor`
- `volumeTextColor`
---
## 4. Screener Table
- `showScreener`: display the screener table
- `tablePosition`: table position (`Top Left`, `Top Right`, `Bottom Left`, `Bottom Right`)
- `tableSize`: table size (`Small`, `Normal`, `Large`)
The table shows:
- Symbol, Timeframe
- Type and status of Order Block
- Number of retests
- Bullish and bearish volumes
---
## 5. Trend Filters
- EMA as a trend filter (`emaPeriod`, default 223)
- `bullishTrend` if close > EMA
- `bearishTrend` if close < EMA
---
## 6. ATR and Swing Points
- ATR calculated with a customizable period (`atrLength`)
- Swing High/Low for SL/TP calculation
- `f_getSwingTargets` function to calculate SL and TP based on direction
---
## 7. Trade Logic
### Buy Limit on Bullish OB
- Conditions:
- New bullish block
- Uptrend
- RR > threshold (`rr_threshold`)
- SL: `bullishOBPrice * (1 - atr * atrMultiplier)`
- Multiple TPs: TP1 (50%), TP2 (80%), TP3 (100% max)
- Quantity calculation based on percentage risk
### Sell Limit on Bearish OB
- Conditions:
- New bearish block
- Downtrend
- RR > threshold (`rr_threshold`)
- SL: `bearishOBPrice * (1 + atr * atrMultiplier)`
- Multiple TPs: TP1 (50%), TP2 (80%), TP3 (100% max)
- Quantity calculation based on percentage risk
---
## 8. Order Management and Timeout
- Close pending orders after `maxPendingBars` bars
- Close open positions after `maxBarsOpen` bars
- Label management for open orders
---
## 9. Alert Conditions
- `bull_touch`: price inside maximum bullish volume zone
- `bear_touch`: price inside maximum bearish volume zone
- `bull_reject`: confirmation of bullish zone rejection
- `bear_reject`: confirmation of bearish zone rejection
- `new_bull`: new bullish block
- `new_bear`: new bearish block
---
## 10. Level Calculation
- Swing levels based on selected timeframe (`SelectPeriod`)
- `xHigh` and `xLow` for S1 and R1 calculation
- Levels plotted on chart
---
## 11. Take Profit / Stop Loss
- Extended horizontal lines (`extendBars`) to visualize TP and SL
- Customizable colors (`tpColor`, `slColor`)
---
## 12. Notes
- Complete script based on Pine Script v5
- Advanced graphical management with boxes, lines, labels
- Dynamically displays volumes and Order Blocks
- Integrated internal screener
---
### End of Documentation
Momentum Variance OscillatorWhat MVO measures:
-PV (Price-Volume) Oscillator – how far price is from a volatility-scaled basis, then weighted by relative volume.
- > 0 = bullish pressure; < 0 = bearish pressure.
-|PV| larger ⇒ stronger momentum.
-Signal line (EMA of PV) – a smoother track of PV; crossings flag momentum shifts.
-Zero line gradient – instantly shows direction (greenish bull / reddish bear) and strength (paler → stronger).
-Extreme bands (±obLevel) – “hot zone” thresholds; being beyond them = exceptional push.
-Variance histogram – MACD-like view (PV minus slower PV-EMA) to see thrust building vs. fading.
-(Optional) Bar coloring & background tint – paints price bars and/or the panel on key events so you can read the regime at a glance.
-Auto-Tune – searches a grid of (obLevel, weakLvl) pairs and (optionally) auto-applies the best, ranked by CAGR vs. drawdown.
Core signals & how to trade them:
1) Define the regime:
-Bullish regime: PV above 0 and/or PV above Signal; zero line is in bull gradient.
-Bearish regime: PV below 0 and/or PV below Signal; zero line is in bear gradient.
-Action: Prefer trades with the regime (avoid fading strong color/strength unless you have a clear reversal setup).
2) Entries:
Momentum entry:
-Long: PV crosses above Signal while PV > 0.
-Short: PV crosses below Signal while PV < 0.
Breakout/acceleration:
-Long add-on: PV crosses above +obLevel (extreme top) and holds.
-Short add-on: PV crosses below −obLevel (extreme bottom) and holds.
-Histogram confirm: Growing bars in your direction = thrust improving; shrinking/flip = thrust stalling.
3) Exits / risk:
-Soft exit / tighten stops: PV loses the extreme and re-enters inside, or histogram fades/turns against you.
-Hard exit / reverse: Opposite PV↔Signal crossover and PV crosses the zero line.
-Weak zone filter: If |PV| < weakLvl, treat signals as lower quality (smaller size or skip).
4) Practical setup - Suggested defaults (good starting point):
-Signal length: 26
-Volume power: 0.50
-obLevel (extreme): 2.00
-weakLvl: 0.75
-Show histogram & dots: On
-Auto-Tune (recommended)
-Turn Auto-Select Best ON. MVO will scan obLevel 1.50→3.00 (step 0.05) and weakLvl 0.50→1.00 (step 0.05), then use the top-ranked pair (CAGR/(1+MDD)).
-If you want to see the top combos, enable the Optimizer Table (Top-3).
5) Visual options
-Bar Colors: Regime+Strength – bars follow the zero-line gradient (great for quick read).
-Extremes – paint only when beyond ±obLevel.
-Cross Signals – paint only on the bar that crosses an extreme.
-Background on breach: A one-bar tint when PV crosses an extreme.
6) Example playbook:
Long setup:
-Zero line shows bull gradient and PV > 0.
-PV crosses above Signal (entry).
-If PV drives above +obLevel, consider add-on; trail under the last minor swing or use ATR.
-Exit/trim on PV crossing below Signal or histogram turning negative; flatten on a drop through 0.
Short setup mirrors the above on the bear side.
7) Tips to avoid common traps:
-Don’t fade strong extremes without clear confirmation (e.g., PV re-entering inside + histogram flip).
-Respect the weak zone: if |PV| < weakLvl, signals are fragile—size down or wait.
-Align with structure: higher-timeframe trend and SR improve expectancy.
-Instrument personality matters: use Auto-Tune or re-calibrate obLevel/weakLvl across assets/timeframes.
8) Alerts you can set:
-Bull Signal X – PV crossed above Signal
-Bear Signal X – PV crossed below Signal
-Bull Baseline X – PV crossed above 0
-Bear Baseline X – PV crossed below 0
QQQ Ladder → Adjusted to Active Ticker (5s & 10s)This indicator allows you to a grid of QQQ levels directly on futures chart like NQ, MNQ, ES and MES, automatically adjusting for the spread between the displayed symbol and QQQ. This is particularly useful for traders who perform technical analysis on QQQ but execute trades on Futures.
Features:
Renders every 5 and 10 points steps of QQQ in your current chart.
The script adjusts these levels in real-time based on the current spread between QQQ and the displayed symbol!
Plots updated horizontal lines that move with the spread
Supports Multiple Tickers, ES1!, MES1!, NQ1!, MNQ1! SPY and SPX500USD.
NDX Ladder → Adjusted to Active Ticker (5s & 10s)This indicator allows you to a grid of NDX levels directly on the NQ! (E-mini NASDAQ 100 Futures) chart, automatically adjusting for the spread between NDX and NQ1!. This is particularly useful for traders who perform technical analysis on SPX but execute trades on NQ1!.
Features:
Renders every 5 and 10 points steps of the NDX in your current chart.
The script adjusts these levels in real-time based on the current spread between NDX and NQ / MNQ
Plots updated horizontal lines that move with the spread
Bot Analyzer📌 Script Name: Bot Analyzer
This TradingView Pine Script v5 indicator creates a dashboard table on the chart that helps you analyze any asset for running a martingale grid bot on futures.
🔧 User Inputs
TP % (tpPct): Take Profit percentage.
SO step % (soStepPct): Step size between safety orders.
SO n (soCount): Number of safety orders.
M mult (martMult): Martingale multiplier (how much each next order increases in size).
Lev (leverage): Leverage used in futures.
BB len / BB mult: Bollinger Bands settings for measuring channel width.
ATR len: ATR period for volatility.
HV days: Lookback window (days) for Historical Volatility calculation.
📐 Calculations
ATR % (atrPct): Normalized ATR relative to price.
Bollinger Band width % (bbPct): Market channel width as percentage of basis.
Historical Volatility (hvAnn): Annualized volatility, calculated from daily log returns.
Dynamic Step % (dynStepPct): Step size for safety orders, automatically adjusted from ATR and clamped between 0.3% and 5%.
Covered Move % (coveredPct): Total percentage move the bot can withstand before last safety order.
Martingale Size Factor (sizeFactor): Total position size multiplier after all safety orders, based on martingale multiplier.
Risk Score (riskLabel): Simple risk estimate:
Low if risk < 30
Mid if risk < 60
High if risk ≥ 60
📊 Output (Table on Chart)
At the top-right of the chart, the script draws a table with 9 rows:
Metric Value
BB % Bollinger Band width in %
HV % Historical Volatility (annualized %)
TP % Take profit setting
SO step % Safety order step size
SO n Number of safety orders
M mult Martingale multiplier
Dyn step % Dynamic step based on ATR
Size x Total position size factor (e.g., 4.5x)
Risk Risk label (Low / Mid / High)
⚙️ Use Case
Helps choose coins for a martingale bot:
If BB% is wide and HV% is high → the asset is volatile enough.
If Risk shows "High" → parameters are aggressive, you may need to adjust step size, SO count, or leverage.
The dashboard lets you compare assets quickly without switching between multiple indicators.
SPX Ladder → Adjusted to Active Ticker (5s & 10s)This indicator allows you to a grid of SPX levels directly on the ES1! (E-mini S&P 500 Futures) chart, automatically adjusting for the spread between SPX and ES1!. This is particularly useful for traders who perform technical analysis on SPX but execute trades on ES1!.
Features:
Renders every 5 and 10 points steps of the SPX in your current chart.
The script adjusts these levels in real-time based on the current spread between SPX and ES1!
Plots updated horizontal lines that move with the spread
Supports Multiple Tickers, ES1!, SPY and SPX500USD.
Ideal for futures traders who want SPX context while trading ES1!.
Perfect Price-Anchored % Fib Grid This indicator generates support and resistance levels anchored to a fixed price of your choice.
You can also specify a percentage for the indicator to calculate potential highs and lows.
Commonly used values are 3.5% or 7%, as well as smaller decimal versions like 0.35% or 0.7%, depending on the volatility you expect.
In addition, the indicator can highlight potential stop-run levels in multiples of 27 — ranging from 0 up to 243. This automatically places the 243 GB range directly onto your chart.
The tool is versatile and can be applied not only to equities, but also to ES futures and Forex markets.
How to Reposition A Table CellOVERVIEW
Using table functions in Pine Script is one of the most effective methods for reporting and interpreting data in a readable manner. However, the built-in capabilities for dynamically repositioning table location are limited. To extend these limitations, a small intervention to the script may be required. This indicator exemplifies how such intervention can be modeled.
CONCEPTS
This indicator provides comprehensive control over table positioning through several user-defined parameters that work together to create flexible display options.
Text Parameters : These five string inputs allow users to define the content displayed in the table. Each parameter accepts custom text that will be displayed as separate rows within the table cell. (The relevant parameters are designed as examples. When implementing the code into your own scripts, you can use series string variables instead of the those inputs.)
Horizontal Offset : This integer parameter controls the horizontal positioning of the table content. Negative values shift the table content to the left, while positive values move it to the right. The offset is multiplied by a spacing factor (currently set to 4) to provide more noticeable movement. This parameter is particularly useful when you need to avoid overlapping with other chart elements or align multiple indicators.
Vertical Offset : This integer parameter manages the vertical positioning by adding line breaks above or below the content. Negative values push the content downward by adding line breaks at the beginning, while positive values elevate the content by adding line breaks at the end. This creates effective vertical spacing without affecting the table's base position.
Table Position : This parameter accepts values from 1 to 9, corresponding to the standard TradingView table positions arranged in a 3x3 grid format (1-3: top row, 4-6: middle row, 7-9: bottom row). This serves as the base positioning before any offset adjustments are applied, providing users with familiar reference points for initial placement.
FUNCTION
The core functionality centers on the custom f_position() function, which processes text positioning based on horizontal and vertical offset values. For vertical positioning, it adds line breaks before or after content depending on the offset direction. For horizontal positioning, it splits the text by rows and adds calculated spaces to each row, maintaining proper alignment across multi-line content. The spacing uses a fixed multiplier of 4, providing good balance between precision and visible movement.
ORIGINALITY & NOTES
Tihs indicator,
introduces a novel approach to table positioning that goes beyond TradingView's standard 9-position limitation by implementing custom offset calculations that allow pixel-level control over table placement.
serves as an educational resource, demonstrating advanced Pine Script techniques for UI manipulation that can be adapted for various custom indicator developments.
is particularly valuable for developers creating complex dashboard layouts or educational materials where precise positioning is crucial. The modular design of the positioning function makes it easily adaptable for other projects requiring similar functionality.
I hope it helps everyone, Always combine with risk management principles and market context awareness. I hope it helps everyone. Trade as safely as possible. Best of luck!
SMC - Institutional Confidence Oscillator [PhenLabs]📊 Institutional Confidence Oscillator
Version: PineScript™v6
📌 Description
The Institutional Confidence Oscillator (ICO) revolutionizes market analysis by automatically detecting and evaluating institutional activity at key support and resistance levels using our own in-house detection system. This sophisticated indicator combines volume analysis, volatility measurements, and mathematical confidence algorithms to provide real-time readings of institutional sentiment and zone strength.
Using our advanced thin liquidity detection, the ICO identifies high-volume, narrow-range bars that signal institutional zone formation, then tracks how these zones perform under market pressure. The result is a dual-wave confidence oscillator that shows traders when institutions are actively defending price levels versus when they’re abandoning positions.
The indicator transforms complex institutional behavior patterns into clear, actionable confidence percentiles, helping traders align with smart money movements and avoid common retail trading pitfalls.
🚀 Points of Innovation
Automated thin liquidity zone detection using volume threshold multipliers and zone size filtering
Dual-sided confidence tracking for both support and resistance levels simultaneously
Sigmoid function processing for enhanced mathematical accuracy in confidence calculations
Real-time institutional defense pattern analysis through complete test cycles
Advanced visual smoothing options with multiple algorithmic methods (EMA, SMA, WMA, ALMA)
Integrated momentum indicators and gradient visualization for enhanced signal clarity
🔧 Core Components
Volume Threshold System: Analyzes volume ratios against baseline averages to identify institutional activity spikes
Zone Detection Algorithm: Automatically identifies thin liquidity zones based on customizable volume and size parameters
Confidence Lifecycle Engine: Tracks institutional defense patterns through complete observation windows
Mathematical Processing Core: Uses sigmoid functions to convert raw market data into normalized confidence percentiles
Visual Enhancement Suite: Provides multiple smoothing methods and customizable display options for optimal chart interpretation
🔥 Key Features
Auto-Detection Technology: Automatically scans for institutional zones without manual intervention, saving analysis time
Dual Confidence Tracking: Simultaneously monitors both support and resistance institutional activity for comprehensive market view
Smart Zone Validation: Evaluates zone strength through volume analysis, adverse excursion measurement, and defense success rates
Customizable Parameters: Extensive input options for volume thresholds, observation windows, and visual preferences
Real-Time Updates: Continuously processes market data to provide current institutional confidence readings
Enhanced Visualization: Features gradient fills, momentum indicators, and information panels for clear signal interpretation
🎨 Visualization
Dual Oscillator Lines: Support confidence (cyan) and resistance confidence (red) plotted as percentage values 0-100%
Gradient Fill Areas: Color-coded regions showing confidence dominance and strength levels
Reference Grid Lines: Horizontal markers at 25%, 50%, and 75% levels for easy interpretation
Information Panel: Real-time display of current confidence percentiles with color-coded dominance indicators
Momentum Indicators: Rate of change visualization for confidence trends
Background Highlights: Extreme confidence level alerts when readings exceed 80%
📖 Usage Guidelines
Auto-Detection Settings
Use Auto-Detection
Default: true
Description: Enables automatic thin liquidity zone identification based on volume and size criteria
Volume Threshold Multiplier
Default: 6.0, Range: 1.0+
Description: Controls sensitivity of volume spike detection for zone identification, higher values require more significant volume increases
Volume MA Length
Default: 15, Range: 1+
Description: Period for volume moving average baseline calculation, affects volume spike sensitivity
Max Zone Height %
Default: 0.5%, Range: 0.05%+
Description: Filters out wide price bars, keeping only thin liquidity zones as percentage of current price
Confidence Logic Settings
Test Observation Window
Default: 20 bars, Range: 2+
Description: Number of bars to monitor zone tests for confidence calculation, longer windows provide more stable readings
Clean Break Threshold
Default: 1.5 ATR, Range: 0.1+
Description: ATR multiple required for zone invalidation, higher values make zones more persistent
Visual Settings
Smoothing Method
Default: EMA, Options: SMA/EMA/WMA/ALMA
Description: Algorithm for signal smoothing, EMA responds faster while SMA provides more stability
Smoothing Length
Default: 5, Range: 1-50
Description: Period for smoothing calculation, higher values create smoother lines with more lag
✅ Best Use Cases
Trending market analysis where institutional zones provide reliable support/resistance levels
Breakout confirmation by validating zone strength before position entry
Divergence analysis when confidence shifts between support and resistance levels
Risk management through identification of high-confidence institutional backing
Market structure analysis for understanding institutional sentiment changes
⚠️ Limitations
Performs best in liquid markets with clear institutional participation
May produce false signals during low-volume or holiday trading periods
Requires sufficient price history for accurate confidence calculations
Confidence readings can fluctuate rapidly during high-impact news events
Manual fallback zones may not reflect actual institutional activity
💡 What Makes This Unique
Automated Detection: First Pine Script indicator to automatically identify thin liquidity zones using sophisticated volume analysis
Dual-Sided Analysis: Simultaneously tracks institutional confidence for both support and resistance levels
Mathematical Precision: Uses sigmoid functions for enhanced accuracy in confidence percentage calculations
Real-Time Processing: Continuously evaluates institutional defense patterns as market conditions change
Visual Innovation: Advanced smoothing options and gradient visualization for superior chart clarity
🔬 How It Works
1. Zone Identification Process:
Scans for high-volume bars that exceed the volume threshold multiplier
Filters bars by maximum zone height percentage to identify thin liquidity conditions
Stores qualified zones with proximity threshold filtering for relevance
2. Confidence Calculation Process:
Monitors price interaction with identified zones during observation windows
Measures volume ratios and adverse excursions during zone tests
Applies sigmoid function processing to normalize raw data into confidence percentiles
3. Real-Time Analysis Process:
Continuously updates confidence readings as new market data becomes available
Tracks institutional defense success rates and zone validation patterns
Provides visual and numerical feedback through the oscillator display
💡 Note:
The ICO works best when combined with traditional technical analysis and proper risk management. Higher confidence readings indicate stronger institutional backing but should be confirmed with price action and volume analysis. Consider using multiple timeframes for comprehensive market structure understanding.
Offset Strike LinesOffset Strike Lines (OSL) is a tool designed to plot strike-based grid levels by offsetting one symbol against another. It compares two instruments (for example, futures vs. index) and projects evenly spaced horizontal lines above and below a calculated reference price. Each line is annotated with the adjusted counter-symbol price, making it easy to visualize relative levels across markets. Customization options include interval size, number of lines, text size, line and text colors — giving traders a clear, flexible framework for mapping out strike zones and price relationships.
Guitar Hero [theUltimator5]The Guitar Hero indicator transforms traditional oscillator signals into a visually engaging, game-like display reminiscent of the popular Guitar Hero video game. Instead of standard line plots, this indicator presents oscillator values as colored segments or blocks, making it easier to quickly identify market conditions at a glance.
Choose from 8 different technical oscillators:
RSI (Relative Strength Index)
Stochastic %K
Stochastic %D
Williams %R
CCI (Commodity Channel Index)
MFI (Money Flow Index)
TSI (True Strength Index)
Ultimate Oscillator
Visual Display Modes
1) Boxes Mode : Creates distinct rectangular boxes for each bar, providing a clean, segmented appearance. (default)
This visual display is limited by the amount of box plots that TradingView allows on each indictor, so it will only plot a limited history. If you want to view a similar visual display that has minor breaks between boxes, then use the fill mode.
2) Fill Mode : Uses filled areas between plot boundaries.
Use this mode when you want to view the plots further back in history without the strict drawing limitations.
Five-Level Color-Coded System
The indicator normalizes all oscillator values to a 0-100 scale and categorizes them into five distinct levels:
Level 1 (Red): Very Oversold (0-19)
Level 2 (Orange): Oversold (20-29)
Level 3 (Yellow): Neutral (30-70)
Level 4 (Aqua): Overbought (71-80)
Level 5 (Lime): Very Overbought (81-100)
Customization Options
Signal Parameters
Signal Length: Primary period for oscillator calculation (default: 14)
Signal Length 2: Secondary period for Stochastic %D and TSI (default: 3)
Signal Length 3: Tertiary period for TSI calculation (default: 25)
Display Controls
Show Horizontal Reference Lines: Toggle grid lines for better level identification
Show Information Table: Display current signal type, value, and normalized value
Table Position: Choose from 9 different screen positions for the info table
Display Mode: Switch between Boxes and Fills visualization
Max Bars to Display: Control how many historical bars to show (50-450 range)
Normalization Process
The indicator automatically normalizes different oscillator ranges to a consistent 0-100 scale:
Williams %R: Converts from -100/0 range to 0-100
CCI: Maps typical -300/+300 range to 0-100
TSI: Transforms -100/+100 range to 0-100
Other oscillators: Already use 0-100 scale (RSI, Stochastic, MFI, Ultimate Oscillator)
This was designed as an educational tool
The gamified approach makes learning about oscillators more engaging for new traders.
Machine Learning BBPct [BackQuant]Machine Learning BBPct
What this is (in one line)
A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system.
Background: %B in plain terms
Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes.
Why add (simplified) KNN?
Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas:
• Feature vector . Each bar is summarized by up to five normalized features:
– %B itself (normalized)
– Band width (volatility proxy)
– Price momentum (ROC)
– Volume momentum (ROC of volume)
– Price position within the bands
• Distance metric . Euclidean distance ranks the most similar recent bars.
• Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance.
• Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence.
This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration.
How the script is organized (by input groups)
1) BBPct Settings
• Price Source – Which price to evaluate (%B is computed from this).
• Calculation Period – Lookback for SMA basis and standard deviation.
• Multiplier – Standard deviation width (e.g., 2.0).
• Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B.
2) Thresholds
• Overbought/Oversold – Default 0.8 / 0.2 (inside ).
• Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions.
3) KNN Machine Learning
• Enable KNN – Switch between pure %B and hybrid.
• K (neighbors) – How many historical analogs to blend (default 8).
• Historical Period – Size of the search window for neighbors.
• ML Weight – Blend between raw %B and KNN estimate.
• Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows.
4) Filtering
• Method – None, Adaptive, Kalman-style (first-order),
or Hull smoothing.
• Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate.
5) Performance Tracking
• Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest).
• Early Entry Lookback – Horizon for forecasting a potential threshold cross.
• Profit Target / Stop Loss – Used only by the internal win-rate heuristic.
6) Self-Optimization
• Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes).
• Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is.
• Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3).
7) UI Settings
• Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays.
• Signal Line Width, Candle Painting, Colors – Visual preferences.
Step-by-step logic
A) Compute %B
Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev.
%B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB .
B) Build the feature vector
All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5).
C) Find nearest neighbors
For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K .
D) Predict and blend
Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient.
E) Adaptive thresholds
Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes.
F) Early entry heuristic
A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself.
G) Informational win-rate
The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest.
Outputs and visual language
• ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering.
• Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline.
• Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes.
• ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7.
• Early arrows – Optional small triangles for approaching OB/OS.
• Candle painting – Light green above the midline, light red below (optional).
• Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed.
Signal classification (informational)
The indicator does not fire trade commands; it labels state:
• STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds.
• BUY / SELL – finalBB beyond adaptive OS/OB.
• EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence.
• NEUTRAL – between adaptive bands.
Alerts (what you can automate)
• Entering adaptive OB/OS and extreme OB/OS.
• Midline cross (0.5).
• Overfitting detected (frequent parameter flipping).
• Early signals when early confidence > 0.7.
These are purely descriptive triggers around the indicator’s state.
Practical interpretation
• Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B.
• Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts.
• Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag.
• Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools.
• Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop.
Methodological notes
• Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that.
• Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts.
• Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias.
• Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA.
• Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator.
• Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative.
Limitations and cautions
• Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks).
• Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare.
• Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail.
• Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest.
• Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives.
Tuning guide
• Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength.
• Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest.
• Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges.
• Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes.
How to use it responsibly
Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation.
Summary
Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
Fibo Swing MFI by julzALGOOVERVIEW
Fibo Swing MFI by julzALGO blends MFI → RSI → Least-Squares smoothing to flag overbought/oversold swings and continuously plot Fibonacci retracements from the rolling high/low of the last 200 bars. It’s built to spot momentum shifts while giving you a clean, always-current fib map of the recent market range.
CORE PRINCIPLES
Hybrid Momentum Signal
- Uses MFI to integrate price and volume.
- Applies RSI to MFI for momentum clarity.
- Smooths the result with Least Squares regression to reduce noise.
Swing Identification
- Marks potential swing highs when momentum is overbought.
- Marks potential swing lows when momentum is oversold.
Fixed-Window Fibonacci Mapping
- Always calculates fib levels from the highest high and lowest low of the last 200 bars.
- This keeps fib zones consistent, independent of swing point detection.
Visual Clarity & Non-Repainting Logic
- Clean labels for OB/OS zones.
- Lines and levels update only as new bars confirm changes.
Adaptability
- Works on any market and timeframe.
- Adjustable momentum length, OB/OS thresholds, and smoothing.
HOW IT WORKS
- Computes Money Flow Index (MFI) from price & volume.
- Applies RSI to the MFI for clearer OB/OS momentum.
- Smooths the hybrid with a Least Squares (linear regression) filter.
- Swing labels appear when OB/OS conditions are met (green = swing low, red = swing high).
- Fibonacci retracements are always drawn from the highest high and lowest low of the last 200 bars (rolling window), independent of swing labels.
HOW TO USE
- Watch for OB/OS flips to mark potential swing highs/lows.
- Use the 200-bar fib grid as your active map of pullback levels and reaction zones.
- Combine fib reactions with your price action/volume cues for confirmation.
- Works across markets and timeframes.
SETTINGS
- Length – Period for both MFI and RSI.
- OB/OS Levels – Overbought/oversold thresholds (default 70/30).
- Smooth – Least-Squares smoothing length.
- Fibonacci Window – Fixed at 200 bars in this version (changeable in code via fibLen).
NOTES
- Logic is non-repainting aside from standard bar/label confirmation.
- Increase Length on very low timeframes to reduce noise.
- Swing labels help context; fibs are always based on the most recent 200-bar high/low range.
SUMMARY
Fibo Swing MFI by julzALGO is a momentum-plus-price action tool that merges MFI → RSI → smoothing to identify overbought/oversold swings and automatically plot Fibonacci retracements based on the rolling high/low of the last 200 bars. It’s designed to help traders quickly see potential reversal points and pullback zones, offering visual confluence between momentum shifts and fixed-window price structure.
DISCLAIMER
For educational purposes only. Not financial advice. Trade responsibly with proper risk management.
All-Time High/Low Levels with Dynamic Price Zones📈 All-Time High/Low Levels with Dynamic Price Zones — AlertBlake
🧠 Overview:
This powerful indicator automatically identifies and draws the All-Time High (AT.H) and All-Time Low (AT.L) on your chart, providing a clear visual framework for price action analysis. It also calculates and displays the Midpoint (50%), Upper Quartile (75%), and Lower Quartile (25%) levels, creating a dynamic grid that helps traders pinpoint key psychological levels, support/resistance zones, and potential breakout or reversal areas.
✨ Features:
Auto-Detection of All-Time High and Low:
Tracks the highest and lowest prices in the full visible historical range of the chart.
Automatically updates as new highs or lows are created.
Dynamic Level Calculation:
Midpoint (50%): Halfway between AT.H and AT.L.
25% Level: 25% between AT.L and AT.H.
75% Level: 75% between AT.L and AT.H.
Each level is clearly labeled with its corresponding value.
Labels are positioned to the right of the price for easy reading.
Color-Coded Lines (customizable)
Correlation HeatMap [TradingFinder] Sessions Data Science Stats🔵 Introduction
n financial markets, correlation describes the statistical relationship between the price movements of two assets and how they interact over time. It plays a key role in both trading and investing by helping analyze asset behavior, manage portfolio risk, and understand intermarket dynamics. The Correlation Heatmap is a visual tool that shows how the correlation between multiple assets and a central reference asset (the Main Symbol) changes over time.
It supports four market types forex, stocks, crypto, and a custom mode making it adaptable to different trading environments. The heatmap uses a color-coded grid where warmer tones represent stronger negative correlations and cooler tones indicate stronger positive ones. This intuitive color system allows traders to quickly identify when assets move together or diverge, offering real-time insights that go beyond traditional correlation tables.
🟣 How to Interpret the Heatmap Visually ?
Each cell represents the correlation between the main symbol and one compared asset at a specific time.
Warm colors (e.g. red, orange) suggest strong negative correlation as one asset rises, the other tends to fall.
Cool colors (e.g. blue, green) suggest strong positive correlation both assets tend to move in the same direction.
Lighter shades indicate weaker correlations, while darker shades indicate stronger correlations.
The heatmap updates over time, allowing users to detect changes in correlation during market events or trading sessions.
One of the standout features of this indicator is its ability to overlay global market sessions such as Tokyo, London, New York, or major equity opens directly onto the heatmap timeline. This alignment lets traders observe how correlation structures respond to real-world session changes. For example, they can spot when assets shift from being inversely correlated to moving together as a new session opens, potentially signaling new momentum or macro flow. The customizable symbol setup (including up to 20 compared assets) makes it ideal not only for forex and crypto traders but also for multi-asset and sector-based stock analysis.
🟣 Use Cases and Advantages
Analyze sector rotation in equities by tracking correlation to major indices like SPX or DJI.
Monitor altcoin behavior relative to Bitcoin to find early entry opportunities in crypto markets.
Detect changes in currency alignment with DXY across trading sessions in forex.
Identify correlation breakdowns during market volatility, signaling possible new trends.
Use correlation shifts as confirmation for trade setups or to hedge multi-asset exposure
🔵 How to Use
Correlation is one of the core concepts in financial analysis and allows traders to understand how assets behave in relation to one another. The Correlation Heatmap extends this idea by going beyond a simple number or static matrix. Instead, it presents a dynamic visual map of how correlations shift over time.
In this indicator, a Main Symbol is selected as the reference point for analysis. In standard modes such as forex, stocks, or crypto, the symbol currently shown on the main chart is automatically used as the main symbol. This allows users to begin correlation analysis right away without adjusting any settings.
The horizontal axis of the heatmap shows time, while the vertical axis lists the selected assets. Each cell on the heatmap shows the correlation between that asset and the main symbol at a given moment.
This approach is especially useful for intermarket analysis. In forex, for example, tracking how currency pairs like OANDA:EURUSD EURUSD, FX:GBPUSD GBPUSD, and PEPPERSTONE:AUDUSD AUDUSD correlate with TVC:DXY DXY can give insight into broader capital flow.
If these pairs start showing increasing positive correlation with DXY say, shifting from blue to light green it could signal the start of a new phase or reversal. Conversely, if negative correlation fades gradually, it may suggest weakening relationships and more independent or volatile movement.
In the crypto market, watching how altcoins correlate with Bitcoin can help identify ideal entry points in secondary assets. In the stock market, analyzing how companies within the same sector move in relation to a major index like SP:SPX SPX or DJ:DJI DJI is also a highly effective technique for both technical and fundamental analysts.
This indicator not only visualizes correlation but also displays major market sessions. When enabled, this feature helps traders observe how correlation behavior changes at the start of each session, whether it's Tokyo, London, New York, or the opening of stock exchanges. Many key shifts, breakouts, or reversals tend to happen around these times, and the heatmap makes them easy to spot.
Another important feature is the market selection mode. Users can switch between forex, crypto, stocks, or custom markets and see correlation behavior specific to each one. In custom mode, users can manually select any combination of symbols for more advanced or personalized analysis. This makes the heatmap valuable not only for forex traders but also for stock traders, crypto analysts, and multi-asset strategists.
Finally, the heatmap's color-coded design helps users make sense of the data quickly. Warm colors such as red and orange reflect stronger negative correlations, while cool colors like blue and green represent stronger positive relationships. This simplicity and clarity make the tool accessible to both beginners and experienced traders.
🔵 Settings
Correlation Period: Allows you to set how many historical bars are used for calculating correlation. A higher number means a smoother, slower-moving heatmap, while a lower number makes it more responsive to recent changes.
Select Market: Lets you choose between Forex, Stock, Crypto, or Custom. In the first three options, the chart’s active symbol is automatically used as the Main Symbol. In Custom mode, you can manually define the Main Symbol and up to 20 Compared Symbols.
Show Open Session: Enables the display of major trading sessions such as Tokyo, London, New York, or equity market opening hours directly on the timeline. This helps you connect correlation shifts with real-world market activity.
Market Mode: Lets you select whether the displayed sessions relate to the forex or stock market.
🔵 Conclusion
The Correlation Heatmap is a robust and flexible tool for analyzing the relationship between assets across different markets. By tracking how correlations change in real time, traders can better identify alignment or divergence between symbols and gain valuable insights into market structure.
Support for multiple asset classes, session overlays, and intuitive visual cues make this one of the most effective tools for intermarket analysis.
Whether you’re looking to manage portfolio risk, validate entry points, or simply understand capital flow across markets, this heatmap provides a clear and actionable perspective that you can rely on.
