Zonas de Liquidez Pro + Puntos de GiroAnalysis of Your BTC/USDT 4H Chart
Here’s the breakdown of the liquidity zones shown on your chart and what each element means:
🔴 Resistance Zones (Red Lines)
R 126199.43 – Upper dotted line
Level: ~$126,199
Strength: = Moderate zone
Touch count: 1 touch | 1 rejection
Meaning: Weak resistance, price has only reacted here once.
Dotted line = few historical rejections.
R 111263.81 – Thick solid red line
Level: ~$111,263
Strength: = Strong zone
Touch count: 3 touches | 2 rejections
Meaning: Major resistance level, strongly defended multiple times.
Solid, thicker line = very respected zone.
R 111250.01 – Solid red line (high strength)
Level: ~$111,250
Strength: = Extremely strong
Touch count: 5 touches | 4 rejections
Meaning: This is a critical zone, heavy liquidity stacked here.
Score 19 = institutional-grade liquidity zone.
R 107508.00 – Lower dotted line
Level: ~$107,508
Strength: = Strong zone
Touch count: 4 touches | 1 rejection
Meaning: Previously acting as resistance, now above current price.
💧 “LIQ” Markers – Liquidity Grabs
The yellow LIQ tags signal liquidity grabs.
Pattern detected:
Price taps the strong resistance around $111,263
Wicks above → triggers stop-losses
Closes back below → fake breakout
High volume → institutional stop-hunting
This led directly to the strong downside move.
🎯 Current Price Context
Current price: ~$91,533
Price is below all major resistance zones
Market structure is bearish
Price is far from major liquidity areas
📉 What Happened
The 111k resistance cluster acted as a massive ceiling
Multiple failed breakouts = institutional selling
Liquidity grabs at the top → trap for late buyers
Price then dumped from $111k to $91k (≈ -18%)
🎲 Probable Scenarios
Bullish Scenario 📈
If price returns to the $107,508 zone → first resistance test
Break with volume → target $111,250
Needs a confirmed close above to validate a breakout
Bearish Scenario 📉
If demand remains weak → continuation lower
Watch for new demand zones forming below price
Rejection from $107k–$111k would confirm bearish continuation
🔍 Key Signals to Watch
Bullish:
Price revisits resistance zone
Liquidity grab below support (fake breakdown)
Strong close back above with volume
Bearish:
New lows below $91k
Volume increasing on down moves
New resistance forming overhead
💡 Trading Approach
If you're a buyer (long bias):
Wait for price to pull into a strong demand zone
Look for bullish rejection + volume
Stop-loss below the zone
If you're a seller (short bias):
Ideal entry already happened at 111k (liquidity trap)
Look for a pullback into $107k–$111k
Watch for bearish rejection signs
Conservative Approach
Don’t trade in the middle of nowhere
Wait for price to reach a liquidity zone
Liquidity zones act as magnets → safest places to form trades
🎓 Key Takeaways
High-score zones like are extremely difficult to break → respect them
Liquidity grabs signaled the reversal perfectly
Strong rejections at 111k = smart money unloading
Thicker solid lines = more reliable levels
In den Scripts nach "bear" suchen
Divergence Detector (MACD + Volume)Divergence Detector (MACD + Volume Confirmation)
This indicator automatically detects bullish and bearish divergences between price and MACD, enhanced with volume confirmation to filter out weak signals.
🔹 Core Logic
Pivot Detection:
The script identifies swing highs and lows (pivots) using customizable left/right lookback values.
Bullish Divergence:
Occurs when price makes a lower low, but MACD makes a higher low.
A label "Bull Div" appears below the bar; if confirmed by high volume, it shows "Bull Div 🔥".
Bearish Divergence:
Occurs when price makes a higher high, but MACD makes a lower high.
A label "Bear Div" appears above the bar; if confirmed by high volume, it shows "Bear Div 📉".
Volume Confirmation:
The indicator checks whether the volume at the pivot bar is above the moving average of volume (customizable length).
This ensures that divergence signals are backed by strong market participation.
Inputs
MACD Fast/Slow/Signal Length – standard MACD parameters
Pivot Lookback Left/Right – defines the swing structure sensitivity
Volume MA Length – defines how volume strength is validated
Output
Labels:
🔹 Bull Div / Bull Div 🔥 → Bullish divergence (confirmed with volume)
🔹 Bear Div / Bear Div 📉 → Bearish divergence (confirmed with volume)
Tips
Works best on higher timeframes and trending markets.
Volume confirmation helps filter false divergences in low liquidity conditions.
Combine with trend or structure indicators for better trade setups.
----------------------------------------------------------------------------------------------
اندیکاتور شناسایی واگرایی MACD با تأیید حجم
این اندیکاتور بهصورت خودکار واگراییهای صعودی و نزولی بین قیمت و MACD را شناسایی کرده و با استفاده از تأیید حجم (Volume Confirmation) سیگنالهای ضعیف را فیلتر میکند.
🔹 منطق عملکرد
شناسایی پیوتها:
نقاط چرخش (سقف و کف) با استفاده از تعداد کندلهای قابل تنظیم در دو سمت شناسایی میشوند.
واگرایی صعودی (Bullish):
زمانی که قیمت کف پایینتر و MACD کف بالاتر میسازد.
برچسب "Bull Div" در زیر کندل نمایش داده میشود؛ اگر حجم بالا باشد، با علامت 🔥 مشخص میگردد.
واگرایی نزولی (Bearish):
زمانی که قیمت سقف بالاتر و MACD سقف پایینتر میسازد.
برچسب "Bear Div" در بالای کندل نمایش داده میشود؛ اگر حجم بالا باشد، با 📉 مشخص میگردد.
تأیید حجم:
اگر حجم در کندل پیوت بالاتر از میانگین متحرک حجم باشد، سیگنال معتبرتر در نظر گرفته میشود.
تنظیمات ورودی
تنظیمات MACD (Fast, Slow, Signal)
پارامترهای شناسایی پیوت (Left / Right)
طول میانگین متحرک حجم (Volume MA Length)
خروجیها
Bull Div 🔥 / Bear Div 📉 برای واگراییهای تأییدشده با حجم
Bull Div / Bear Div برای واگراییهای بدون تأیید حجم
نکات کاربردی
بهترین عملکرد در تایمفریمهای بالا و بازارهای دارای روند
تأیید حجم به حذف سیگنالهای اشتباه در شرایط حجم پایین کمک میکند
برای دقت بیشتر، آن را با اندیکاتورهای روند یا ساختار ترکیب کنید
⚠️ Disclaimer:
This script is provided for educational and informational purposes only.
It does not constitute financial advice, and the author is not responsible for any financial losses caused by its use.
Always confirm signals with your own analysis and other tools before making trading decisions.
⚠️ توجه:
این اسکریپت صرفاً جهت آموزش و اطلاعرسانی طراحی شده و توصیه مالی یا سرمایهگذاری محسوب نمیشود.
نویسنده مسئول هیچگونه ضرر یا زیان احتمالی ناشی از استفاده از آن نیست.
لطفاً پیش از هر تصمیم معاملاتی، تحلیل شخصی خود را انجام داده و از این ابزار در کنار سایر ابزارهای تحلیل و مدیریت ریسک استفاده کنید.
Madstrat Strategy - Dual TF# Madstrat Strategy - Dual TF: Complete User Guide
## Overview
The Madstrat Strategy indicator is a comprehensive forex trading system that identifies high-probability trade setups based on a day-counting methodology combined with multi-timeframe EMA alignment analysis. It generates two primary signal types:
1. **Day 3 Signals** - Based on the GSD/RSD (Green Setup Day/Red Setup Day) counting system
2. **Pure Price Action (PA) Signals** - Based on EMA alignment across multiple timeframes with EQ rejection
The indicator operates on **two timeframe combinations simultaneously**:
- **15-minute / 1-hour** combo
- **30-minute / 2-hour** combo
---
## Section 1: Timeframe Signals
### Settings
| Input | Default | Description |
|-------|---------|-------------|
| Show 15m/1hr Signals | ✓ Enabled | Displays signals from the 15-minute LTF with 1-hour HTF confirmation |
| Show 30m/2hr Signals | ✓ Enabled | Displays signals from the 30-minute LTF with 2-hour HTF confirmation |
| Trade Levels Source | Most Recent | Determines which combo draws SL/TP levels |
### How It Works
Each timeframe combination operates independently with its own:
- Signal spacing rules (4 bars for 15m, 2 bars for 30m = both equal ~1 hour)
- Daily signal limits (3 Day 3 signals + 3 Pure PA signals per combo per day)
- EMA alignment checks on both LTF and HTF
**Trade Levels Source Options:**
- **15m/1hr** - Only 15m/1hr signals draw trade levels
- **30m/2hr** - Only 30m/2hr signals draw trade levels
- **Most Recent** - Whichever signal fires most recently draws levels (15m/1hr takes priority if both fire simultaneously)
---
## Section 2: Signal Colors
Customize the appearance of each signal type for each timeframe combination:
### 15m/1hr Combo
| Signal Type | Default Color |
|-------------|---------------|
| Day 3 Buy | Blue |
| Day 3 Sell | Red |
| Pure PA Buy | Aqua |
| Pure PA Sell | Fuchsia |
### 30m/2hr Combo
| Signal Type | Default Color |
|-------------|---------------|
| Day 3 Buy | Teal |
| Day 3 Sell | Orange |
| Pure PA Buy | Lime |
| Pure PA Sell | Maroon |
---
## Section 3: Enhanced FBR Rules
### What is FBR?
**FBR (Failed Breakout Retest)** occurs when price breaks below the previous week's low (or above the previous week's high) but fails to close outside the range, closing back inside instead. This signals a potential reversal and resets the day count to "Day 1" of a new setup sequence.
### Settings
| Input | Default | Description |
|-------|---------|-------------|
| Enable Enhanced FBR Rule | ✓ Enabled | Prevents FBR detection after a clean breakout |
| Show Clean Breakout Labels | ✓ Enabled | Displays labels when clean breakouts occur |
| Bull Breakout Label Color | Blue (25% transparent) | Background color for bullish breakout labels |
| Bear Breakout Label Color | Red (25% transparent) | Background color for bearish breakout labels |
### How Enhanced FBR Works
1. **Clean Breakout Detection**: A clean breakout occurs when price breaks AND closes outside the previous week's range
2. **FBR Blocking**: Once a clean breakout occurs in a week, FBR detection is disabled for the remainder of that week
3. **Weekly Reset**: Both clean breakout and FBR flags reset at the start of each new trading week (Sunday rollover)
### Label Types
- **"CLEAN BULL BO"** - Price broke above previous week high and closed above it
- **"CLEAN BEAR BO"** - Price broke below previous week low and closed below it
- **"FBR Day 1"** - Failed breakout retest detected, count reset to Day 1
---
## Section 4: Real-Time Day Labels
### Purpose
The real-time label shows a **live projection** of what today's day classification will be, updating throughout the trading session as price action develops.
### Settings
| Input | Default | Description |
|-------|---------|-------------|
| Enable Real-Time Day Labels | ✓ Enabled | Shows dynamic label that updates during trading |
| Real-Time Label Position | Right | Position of label relative to current candle |
| Real-Time Label Background | Yellow (20% transparent) | Background color |
| Real-Time Label Text | White | Text color |
### Label Text Meanings
| Label | Meaning |
|-------|---------|
| LIVE: GSD Day X | Projected Green Setup Day (after 2+ red days) |
| LIVE: GD Day X | Projected Green Day (continuing green trend) |
| LIVE: RSD Day X | Projected Red Setup Day (after 2+ green days) |
| LIVE: RD Day X | Projected Red Day (continuing red trend) |
| LIVE: INSIDE DAY | Price range is entirely within previous day's range |
| LIVE: FBR - GSD Day 1 | Bullish failed breakout retest detected |
| LIVE: FBR - RSD Day 1 | Bearish failed breakout retest detected |
| LIVE: ... CLEAN BULL BO | Clean bullish breakout detected |
| LIVE: ... CLEAN BEAR BO | Clean bearish breakout detected |
---
## Section 5: Daily Session Definition
### Instrument Presets
| Preset | Sunday Open | Friday Close | Rollover | Use Case |
|--------|-------------|--------------|----------|----------|
| Forex (FX Pairs) | 17:05 ET | 16:59 ET | 17:00 ET | EUR/USD, GBP/USD, etc. |
| Metals (XAU/XAG) | 18:05 ET | 16:59 ET | 17:00 ET | Gold, Silver |
| Custom | User-defined | User-defined | User-defined | Other instruments |
### Why This Matters
The indicator uses **OANDA-style daily rollover** (5 PM Eastern) rather than UTC midnight. This ensures:
- Accurate day counting for forex markets
- Correct GSD/RSD classification
- Proper weekly level calculations
### Session Break Line
| Input | Default | Description |
|-------|---------|-------------|
| Show Session Break Line | ✓ Enabled | Draws vertical line at daily rollover |
| Session Break Line Color | Black | Line color |
| Width | 2 | Line thickness (1-5) |
| Style | Solid | Solid, dashed, or dotted |
---
## Section 6: Day Labels (GSD/RSD System)
### The Core Day Counting Methodology
This is the foundation of the Madstrat Strategy:
1. **Green Day (GD)**: Daily candle closes higher than it opened
2. **Red Day (RD)**: Daily candle closes lower than it opened
3. **Green Setup Day (GSD)**: A green day that follows 2 or more consecutive red days
4. **Red Setup Day (RSD)**: A red day that follows 2 or more consecutive green days
### The Day 3 Signal
**Day 3** is when the setup is "mature" and ready for a trade:
- **GSD Day 3**: Third consecutive green day after a red sequence of 2+ days
- **RSD Day 3**: Third consecutive red day after a green sequence of 2+ days
### Settings
| Input | Default | Description |
|-------|---------|-------------|
| Max Historical Labels | 60 | Number of day labels to retain on chart |
| Show Day of Week Labels | ✓ Enabled | Shows M O N, T U E, etc. |
| Label Position | Top | Top or bottom of chart |
| Label Hour | 6 | Hour (0-23) when day labels appear |
| GSD/GD Label Background | Blue (25% transparent) | Green day label color |
| RSD/RD Label Background | Red (25% transparent) | Red day label color |
| Inside Day Label Background | Gray (25% transparent) | Inside day label color |
### Important Notes
- **Inside Days** do not increment the count - they are neutral
- **FBR events** reset the count to Day 1 and establish a new trend direction
- **Clean Breakouts** also reset to Day 1 but block further FBR detection that week
---
## Section 7: Daily Levels
Displays the previous day's key price levels:
### Available Levels
| Level | Default | Description |
|-------|---------|-------------|
| Previous Day's High (PDH) | ✓ Enabled, Blue | Highest price of previous session |
| Previous Day's Low (PDL) | ✓ Enabled, Green | Lowest price of previous session |
| Previous Day's EQ | ✓ Enabled, Black | Equilibrium (midpoint of PDH/PDL) |
| 75% Level | ✗ Disabled | 75% of previous day's range |
| 25% Level | ✗ Disabled | 25% of previous day's range |
### EQ Rejection (Critical for Signals)
The **EQ (Equilibrium)** level is crucial for signal generation:
- **Bullish EQ Rejection**: Price wicks down to touch EQ, then closes above it
- **Bearish EQ Rejection**: Price wicks up to touch EQ, then closes below it
The indicator tracks these rejections throughout the day and uses them as a key filter for both Day 3 and Pure PA signals.
---
## Section 8: Weekly Levels
### Previous Week Levels
| Level | Description |
|-------|-------------|
| PWH (Previous Week High) | Highest price of the completed previous week |
| PWL (Previous Week Low) | Lowest price of the completed previous week |
| PWEQ (Previous Week EQ) | Midpoint of PWH and PWL |
### Current Week Levels
| Level | Description |
|-------|-------------|
| WH (Week High) | Running high of the current week |
| WL (Week Low) | Running low of the current week |
| WEQ (Week EQ) | Running midpoint of current week |
### Settings
| Input | Default | Description |
|-------|---------|-------------|
| Show Weekly Levels | ✓ Enabled | Master toggle for all weekly levels |
| Show Previous Week High/Low/EQ | ✓ Enabled | PWH, PWL, PWEQ lines |
| Previous Week Line Color | Black | Color for PW levels |
| Previous Week Line Width | 2 | Thickness of PW lines |
| Show Current Week High/Low | ✓ Enabled | WH, WL lines (dashed) |
| Current Week Line Color | Blue | Color for current week levels |
| Show Weekly Level Labels | ✓ Enabled | Text labels at line ends |
| Weekly Label Size | Normal | Tiny to Huge |
| Lines & Labels End Day | Friday | Extend lines to which day |
---
## Section 9: Session Overlays
Visual boxes showing major forex trading sessions:
### Available Sessions
| Session | Default Times (ET) | Default State |
|---------|-------------------|---------------|
| Sydney | 18:00 - 02:00 | ✗ Disabled |
| Asian | 19:00 - 04:15 | ✓ Enabled |
| London | 01:00 - 11:15 | ✓ Enabled |
| New York | 07:30 - 17:15 | ✓ Enabled |
### Customization Options
For each session:
- Start/End Hour and Minute
- Timezone
- Background color (with transparency)
- Border color
- Border style (solid, dashed, dotted)
- Border width
### General Session Settings
| Input | Default | Description |
|-------|---------|-------------|
| Show Session Overlays | ✓ Enabled | Master toggle |
| Show Session Names on Boxes | ✓ Enabled | Display "Sydney", "Asia", etc. |
| Session Box Border Width | 1 | Border thickness |
| Session Name Text Color | Black | Label text color |
| Session Name Size | Normal | Tiny to Huge |
---
## Section 10: Chart Visuals (Moving Averages)
### Available Moving Averages
| MA | Default | Default Color | Purpose |
|----|---------|---------------|---------|
| 9 EMA | ✓ Shown | Green | Fast trend |
| 18 EMA | ✓ Shown | Orange | Medium trend |
| 50 EMA | ✓ Shown | Blue | Slow trend |
| 50 SMA | ✓ Shown | Purple | Alternative slow trend |
| 200 EMA | ✗ Hidden | Red | Long-term trend |
### EMA Alignment Requirement
For signals to fire, the EMAs must be properly "stacked":
**Bullish Alignment:**
```
Price > 9 EMA > 18 EMA > 50 EMA
```
**Bearish Alignment:**
```
Price < 9 EMA < 18 EMA < 50 EMA
```
This alignment must be present on **both** the LTF (15m or 30m) **and** the HTF (1hr or 2hr) for a signal to generate.
---
## Section 11: Signal Filters
### EQ Rejection Recency
| Input | Default | Description |
|-------|---------|-------------|
| EQ Rejection Recency (bars) | 4 | EQ rejection must occur within this many bars |
On a 15-minute chart, 4 bars = 1 hour. This ensures the EQ rejection is "fresh" and relevant.
### Session Filter
| Input | Default | Description |
|-------|---------|-------------|
| Enable Session Filter | ✗ Disabled | Only allow signals during selected sessions |
| Allow Sydney Session Signals | ✓ Enabled | (Only applies if filter enabled) |
| Allow Asian Session Signals | ✓ Enabled | |
| Allow London Session Signals | ✓ Enabled | |
| Allow New York Session Signals | ✓ Enabled | |
### ADX Filter
| Input | Default | Description |
|-------|---------|-------------|
| Enable ADX Filter | ✓ Enabled | Require minimum trend strength |
| ADX Threshold | 20.0 | Minimum ADX value (5.0 - 50.0) |
The ADX (Average Directional Index) measures trend strength. Values above 20-25 indicate a trending market suitable for directional trades.
---
## Section 12: Signal Types Explained
### Day 3 Signals (Primary)
Day 3 signals come in two forms:
#### Day 3 Detected (Live)
Fires when the **current day is projected** to become Day 3 based on real-time price action. This is an early signal that may change if the daily candle reverses before close.
#### Day 3 Confirmed
Fires when Day 3 has been **officially confirmed** by the previous day's close. This is a more reliable signal as the day count is locked in.
**Requirements for Day 3 Buy:**
1. GSD Count = 3 (confirmed) OR Projected GSD Count = 3 (live)
2. Not an inside day (current or previous)
3. Recent bullish EQ rejection (within recency bars)
4. Bullish EMA alignment on LTF
5. Bullish EMA alignment on HTF
6. Adequate candle body (not all wick)
7. ADX above threshold (if enabled)
8. Within allowed session (if filter enabled)
9. Signal spacing requirement met
10. Less than 3 Day 3 signals already today for this combo
**Day 3 Sell** - Same requirements but bearish (RSD Count = 3, bearish alignment, bearish EQ rejection)
### Pure PA Signals (Secondary)
Pure PA signals also come in two forms:
#### Pure PA Detected (LTF Only)
Fires when the **lower timeframe conditions** are met but HTF confirmation is still pending. This is an early warning that a full signal may be imminent.
#### Pure PA Confirmed (LTF + HTF)
Fires when **both LTF and HTF** conditions are aligned. This is the full confirmation signal.
**Requirements for Pure PA Buy:**
1. Recent bullish EQ rejection
2. Bullish EMA alignment on LTF (Price > 9 > 18 > 50)
3. Bullish EMA alignment on HTF (Price > 9 > 18 > 50)
4. Adequate candle body ratio (≥30%)
5. ADX above threshold on LTF
6. Not currently an inside day
7. Signal spacing requirement met
8. Less than 3 Pure PA signals already today for this combo
9. Within allowed session (if filter enabled)
**Pure PA Sell** - Same requirements but bearish
---
## Section 13: Trade Levels
When a signal fires, the indicator can draw:
| Level | Style | Description |
|-------|-------|-------------|
| Stop Loss (SL) | Red dashed | Entry price ± (ATR × 1.5) |
| Take Profit 1 | Green dashed | 1:1 Risk/Reward |
| Take Profit 2 | Green dotted | 2:1 Risk/Reward |
| Take Profit 3 | Green dotted | 3:1 Risk/Reward |
These levels use a 14-period ATR for the stop loss calculation.
---
## Section 14: Debug Table
Enable **Show Debug Table** to display real-time diagnostic information:
### Information Displayed
| Category | Variables |
|----------|-----------|
| Day Counting | GSD Count, RSD Count, Projected GSD, Projected RSD |
| Day State | Is Projected D3?, Currently Inside?, Week Has FBR?, Clean Breakout (Week)? |
| 15m/1hr Combo | LTF Bull/Bear Positioning, HTF Bull/Bear Positioning, D3/PA Signals Today, Signal Spacing OK |
| 30m/2hr Combo | LTF Bull/Bear Positioning, HTF Bull/Bear Positioning, D3/PA Signals Today, Signal Spacing OK |
| Shared | EQ Rejection Recent (Bull/Bear), Session Filter OK, 15m ADX, 30m ADX, Trade Levels Source |
Green cells = condition met (true)
Red cells = condition not met (false)
Gray cells = informational values
---
## Section 15: Alert Settings
The indicator features a comprehensive **enhanced alert system** with granular control over when and how alerts fire.
### Alert Settings Inputs
| Input | Default | Description |
|-------|---------|-------------|
| Enable Dynamic Alerts | ✓ Enabled | Master toggle for all dynamic alerts with detailed messages |
| Day 3 Detected (Live) | ✓ Enabled | Alert when Day 3 is projected based on current price action |
| Day 3 Confirmed | ✓ Enabled | Alert when Day 3 is officially confirmed |
| Pure PA Detected (LTF) | ✓ Enabled | Alert when LTF conditions are met (early warning) |
| Pure PA Confirmed (LTF+HTF) | ✓ Enabled | Alert when both LTF and HTF conditions align |
### Alert Message Format
All dynamic alerts follow a standardized format for easy parsing:
```
TYPE | SYMBOL @ PRICE | DAY_CLASS | SESSION | DIRECTION | COMBO
```
**Example alerts:**
```
D3 DETECTED | EURUSD @ 1.08542 | GSD Day 3 | London | BUY | 15m/1hr
D3 CONFIRMED | GBPJPY @ 192.456 | RSD Day 3 | New York | SELL | 30m/2hr
PA DETECTED | XAUUSD @ 2345.67 | GSD Day 2 | Asian | BUY | 15m/1hr (LTF only)
PA CONFIRMED | EURJPY @ 164.123 | RSD Day 1 | London | SELL | 30m/2hr
```
### Alert Types Explained
| Alert Type | Meaning | Use Case |
|------------|---------|----------|
| **D3 DETECTED** | Day 3 projected based on current candle | Early entry opportunity; may invalidate if candle reverses |
| **D3 CONFIRMED** | Day 3 locked in from previous close | Higher confidence entry; day count is confirmed |
| **PA DETECTED** | LTF alignment met, waiting for HTF | Heads-up alert; prepare for potential entry |
| **PA CONFIRMED** | Both LTF and HTF aligned | Full confirmation; ready to execute |
### TradingView Alert Dialog Options
When creating an alert in TradingView, you'll see these condition options in the dropdown:
#### Day 3 Detected (Live Projection)
- D3 Detected: Buy 15m/1hr
- D3 Detected: Sell 15m/1hr
- D3 Detected: Buy 30m/2hr
- D3 Detected: Sell 30m/2hr
#### Day 3 Confirmed
- D3 Confirmed: Buy 15m/1hr
- D3 Confirmed: Sell 15m/1hr
- D3 Confirmed: Buy 30m/2hr
- D3 Confirmed: Sell 30m/2hr
#### Pure PA Detected (LTF Only)
- PA Detected: Buy 15m/1hr
- PA Detected: Sell 15m/1hr
- PA Detected: Buy 30m/2hr
- PA Detected: Sell 30m/2hr
#### Pure PA Confirmed (LTF + HTF)
- PA Confirmed: Buy 15m/1hr
- PA Confirmed: Sell 15m/1hr
- PA Confirmed: Buy 30m/2hr
- PA Confirmed: Sell 30m/2hr
#### Combined Alerts (Any Combo)
- D3 Detected: Any Buy
- D3 Detected: Any Sell
- D3 Confirmed: Any Buy
- D3 Confirmed: Any Sell
- PA Confirmed: Any Buy
- PA Confirmed: Any Sell
#### Master Alerts
- ALL Day 3: Any Buy
- ALL Day 3: Any Sell
- ALL PA: Any Buy
- ALL PA: Any Sell
### Setting Up Alerts
1. **Click the Alert icon** in TradingView (or press Alt+A)
2. **Select the indicator** "Madstrat Strategy - Dual TF"
3. **Choose the condition** from the dropdown (e.g., "D3 Confirmed: Any Buy")
4. **Configure notification options** (popup, email, webhook, etc.)
5. **Set alert name** and click "Create"
### Recommended Alert Configurations
**Conservative Approach:**
- Enable only "Day 3 Confirmed" and "PA Confirmed" alerts
- These fire after full confirmation on both timeframes
**Aggressive Approach:**
- Enable all alert types including "Detected" alerts
- Get early warnings but verify manually before entry
**Session-Specific:**
- Create separate alerts for each session you trade
- Use the session filter to limit when signals can fire
---
## Section 16: Signal Identification on Chart
| Shape | Text | Meaning |
|-------|------|---------|
| ▲ Triangle Up | D3-15 | Day 3 Buy from 15m/1hr combo |
| ▲ Triangle Up | D3-30 | Day 3 Buy from 30m/2hr combo |
| ▼ Triangle Down | D3-15 | Day 3 Sell from 15m/1hr combo |
| ▼ Triangle Down | D3-30 | Day 3 Sell from 30m/2hr combo |
| ◆ Diamond | PA-15 | Pure PA signal from 15m/1hr combo |
| ◆ Diamond | PA-30 | Pure PA signal from 30m/2hr combo |
---
## Quick Start Guide
### Recommended Setup for Forex
1. **Timeframe**: Apply indicator to a 15-minute chart
2. **Instrument Preset**: Select "Forex (FX Pairs)"
3. **Enable both** 15m/1hr and 30m/2hr signals initially
4. **Trade Levels Source**: "Most Recent"
5. **ADX Filter**: Enabled with threshold 20
6. **Alerts**: Enable "D3 Confirmed" and "PA Confirmed" for reliable signals
### Reading Signals
1. Look for **Day 3 signals** (triangles) as primary entries
2. Use **Pure PA signals** (diamonds) as supplementary entries
3. Check the debug table to understand why signals did/didn't fire
4. Reference the real-time day label to anticipate upcoming Day 3 opportunities
### Alert Strategy
**For active monitoring:**
- Enable "Detected" alerts as early warnings
- Manually verify conditions before entry
**For set-and-forget:**
- Enable only "Confirmed" alerts
- Trust the full confirmation system
---
## Troubleshooting
### No Signals Appearing?
Check the debug table for:
1. **EQ Rejection Recent** - Is there a recent EQ rejection?
2. **LTF/HTF Positioning** - Are EMAs properly aligned?
3. **GSD/RSD Count** - Is it actually Day 3?
4. **Currently Inside?** - Inside days block signals
5. **Signal Spacing OK** - Has enough time passed since last signal?
6. **ADX value** - Is it above the threshold?
### Day Labels Not Matching Expected Count?
- Verify **Instrument Preset** matches your trading instrument
- Check if an **FBR** or **Clean Breakout** reset the count
- **Inside days** don't increment the count
- Week resets occur at **Sunday 5 PM ET** for forex
### Alerts Not Firing?
1. Ensure **Enable Dynamic Alerts** is checked
2. Verify the specific alert type is enabled (D3 Detected, D3 Confirmed, etc.)
3. Check that the alert condition is properly set up in TradingView
4. Confirm signal filters (session, ADX) aren't blocking the signal
### Understanding Detected vs Confirmed
| Scenario | Detected Alert | Confirmed Alert |
|----------|----------------|-----------------|
| Current day projected to be Day 3, candle still open | ✓ Fires | ✗ Won't fire |
| Previous day closed as Day 3, conditions met today | ✓ May fire | ✓ Fires |
| LTF aligned, HTF not yet aligned | ✓ PA Detected fires | ✗ PA Confirmed won't fire |
| Both LTF and HTF aligned | ✓ May fire | ✓ PA Confirmed fires |
---
## Glossary
| Term | Definition |
|------|------------|
| **GSD** | Green Setup Day - Green day following 2+ red days |
| **RSD** | Red Setup Day - Red day following 2+ green days |
| **GD** | Green Day - Regular green day (not a setup) |
| **RD** | Red Day - Regular red day (not a setup) |
| **FBR** | Failed Breakout Retest - Price breaks weekly level but closes back inside |
| **EQ** | Equilibrium - Midpoint of previous day's range |
| **LTF** | Lower Timeframe (15m or 30m) |
| **HTF** | Higher Timeframe (1hr or 2hr) |
| **PWH/PWL** | Previous Week High/Low |
| **PDH/PDL** | Previous Day High/Low |
| **Clean Breakout** | Price breaks AND closes outside previous week's range |
---
This documentation covers the complete functionality of the Madstrat Strategy - Dual TF indicator including the enhanced alert system. For further assistance with specific scenarios or edge cases, enable the debug table and analyse the real-time variable states.
GardFx - Fusion - ORBFusion ORB & Bias Monitor
This indicator is a comprehensive toolkit designed for session-based traders. It combines an Opening Range Breakout (ORB) visualizer with a Multi-Timeframe (MTF) trend bias dashboard. It is designed to help traders identify key session levels while keeping track of the broader market trend.
How it Works
1. Opening Range Breakout (ORB) Lines The script identifies the High and Low prices established during the first 15 minutes of a specific session or a manually defined start time.
Calculation: The script tracks the high and low values of candles occurring within the 15-minute window defined by the user settings. It then projects these levels forward using line.new.
Reset Logic: The lines automatically reset at the start of a new session (London or New York) or at specific reset times to ensure the chart remains clean for the next trading opportunity.
2. Multi-Timeframe Bias Dashboard The dashboard provides a quick "Bullish" or "Bearish" sentiment check across four timeframes: Daily, 4-Hour, 1-Hour, and 15-Minute.
Methodology: The script uses request.security to fetch the closing price and a 50-period Exponential Moving Average (EMA) for each timeframe.
Signal:
Bullish: Current Close > 50 EMA
Bearish: Current Close < 50 EMA
3. Exchange Clock & Session Tracker A built-in clock displays the current Exchange Time and identifies the active trading session (Asia, London, or New York). This uses timenow and timezone-specific checks to account for Daylight Savings Time shifts between London and New York.
Settings
Automate Session Times: Toggles between automatic detection of London (08:00) and NY (09:30) opens, or a manual user-defined start time.
Manual Start Hour/Minute: Defines the start of the ORB calculation if automation is disabled.
Bias EMA Length: Adjustable length for the trend detection EMA (Default: 50).
Visuals: Users can customize line colors, width, and toggle the mid-line display.
Usage This tool is best used on lower timeframes (e.g., 1-minute or 5-minute) to visualize the 15-minute opening range boundaries. Traders often observe price action around these high/low lines to determine potential breakouts or reversals, using the MTF Dashboard to align trades with the higher timeframe momentum.
RT-Main IndicatorThe RT-Main Indicator is the core indicator that started it all. Developed over more than 5 years, this all in one tool helps traders identify when market participants are buying and selling using multi-colored candles that update in real time. It also identifies key support and resistance levels with Rainbow Pivots and highlights unusual price movements with Whale Print arrows. At its core, the RT-Main Indicator tracks buying and selling with eight colors instead of two, because real world markets are complex and order flow should not be treated as purely binary(Red vs Green).
Introduction
The RT-Main Indicator is designed as a primary Rainbow Theory Tool. It uses color coded candles to show changes in strength, Rainbow Pivots to mark important support and resistance areas, and Whale Prints to flag abnormal buy and sell activity. The goal is to bring these components together into a single framework so traders can read trend, structure, and larger player behavior without stacking many separate indicators.
This tutorial will cover each aspect of the tool:
Colored Candles
Whales are stealth experts and their strength is their ability to not be detected as they move the market. Rainbow Theory illuminates them from the shadows with a spectrum of specifically coded colors to display their unique strengths/weaknesses. In practice, this means the RT-Main Indicator uses internal strength and exhaustion metrics to color candles so that shifts in buying and selling pressure are easier to see.
The base of the RT-Main Indicator is the colored candles it paints onto the chart. These colors automatically tune to the chart based on the timeframe the trader is currently using (1D, H12, H1, 15M, etc). Instead of painting charts with a single Bullish Color (Green) and a single Bearish Color (Red), Rainbow Theory breaks out and identifies these moves into four Bearish Colors (Red|Orange|Yellow|White) and four Bullish Colors (Green|Blue|Purple|Pink). Each color tells a different story of the trend and helps traders better understand the nature of the current trend.
Bullish Colors
#4 - Green Candles - Weakest bullish color, these trends can sustain for extended periods of time.
#3 - Blue Candles - Strong bullish color, a move is starting to develop and can sustain.
#2 - Purple Candles - Second strongest bullish color, Whales are committed to the move but cannot sustain this level of momentum for long durations and a top is near.
#1 - Pink Candles - Strongest bullish color, Whales are using every single ounce of energy they have to push price up, the trend cannot be sustained and its time to take profits.
Bearish Colors
#4 - Red Candles - Weakest bearish color, these trends can sustain for extended periods of time.
#3 - Orange Candles - Strong bearish color, a move is starting to develop and can sustain.
#2 - Yellow Candles - Second strongest bearish color, Whales are committed to the move but cannot sustain this level of momentum for long durations and a bottom is near.
#1 - White Candles - Strongest bearish color, Whales are using every single ounce of energy they have to push price down into all out capitulation, the trend cannot be sustained and its time to look for entries.
How To Enable Colored Candles
By default, the Indicator’s Candles are placed behind the default candles. To properly display them, you must bring them forward. To do this, click the settings icon on the indicator, click visual order and then click bring to front:
Example - Bringing all the colors together into a Bearish Trend that reverses into a Bullish Trend:
The color thresholds can be tuned using the following options:
Automatic Tuning On/Off - Enables or disables the automatic color tuning that adjusts for each timeframe.
Auto Tuning Gain (Inc/Dec) - Increases or decreases how aggressive the automatic tuning algorithm adjusts color tuning.
Manual Fine Tuning - Linear Color Shift - Manually controls the linear sensitivity for color candle thresholds. This can be visualized as a setting being adjusted up or down in a straight, linear fashion. Linear Color Shift
Manual Fine Tuning - Exponential Color Shift - Manually controls the exponential sensitivity for color candle thresholds. This can be visualized as a setting being adjusted in an exponential manner where each level moves in an exponential shift instead of all moving equally. Exponential Color Shift Dark Mode
Some traders prefer light colored backgrounds for their charting, which can make white candles difficult to see. The RT-Main Indicator includes a Dark Mode toggle so colors stay readable on both dark and light charts.
Dark Mode Candles On/Off - Forces the indicator to use the second color set stored in the Style tab in the RT-Main Indicator settings when using light backgrounds. The White/Black Candle can also have a custom color applied if the trader is not content with these two default options.
Custom Candle Colors
In addition to toggling between light and dark modes, each individual color used by the RT-Main Indicator can be edited in the Style tab. This allows traders to keep the same logic while adjusting the visual palette to match their own chart layout.
Rainbow Rotations
Rainbow Rotations are a feature traders use to catch reversals or reversions when a trend fully blows out. The algorithm triggers on the first weaker candle that closes after a Pink or White candle prints. The general idea of this event is to show peaks and valleys of an asset.
In a strong bearish move, White candles mark extreme selling. If a weaker Yellow candle appears after a White candle, that first weaker candle is where the rotation event triggers and a Rainbow Rotation marker is placed on the chart. In a strong bullish move, Pink candles mark extreme buying. The first weaker bullish candle after a Pink candle triggers the opposite side rotation marker.
Note that Rainbow Rotations can only be visible for a finite amount of candles. The Replay function in TradingView can be used to review previous triggers.
Rainbow Rotation settings are available near the top of the settings menu:
Rainbow Rotation Alerts On/Off - Toggles these signals on or off with one click.
Rainbow Rotation Symbol - Customizes the symbol that is plotted on the chart for Rainbow Rotations. Both text and emojis can be used instead of the default symbol.
Rainbow Rotation Alerts
Rainbow Rotations can also be automated with standard TradingView alerts. To set this up:
Click the Alert icon on the right side of the screen.
Change Condition to the RT-Main Indicator.
Change the second condition to one of the three options:
Bullish Alerts | Bearish Alerts | Bearish and Bullish Alerts
Set Trigger to Once Per Bar Close.
Once set up, this allows traders to be notified when the RT-Main Indicator detects an extreme bullish or bearish trend that is starting to reverse.
Automated Pivots
One of the RT-Main Indicator's most powerful functions is the automated support and resistance pivots. This logic uses two internal bots that are tuned to look for potential support and resistance order blocks.
The Resistance Pivot Bot prints lines that are painted with red dashes.
The Support Pivot Bot prints lines that are painted with green dashes.
Regardless of the color of the dashed pivot line, any trend that approaches a pivot should be respected. For example, a trend moving up towards a green support pivot should still treat that area as resistance if price is approaching from below.
As the algorithm continues to print additional pivots on the chart, traders can start identifying order blocks that are otherwise hidden in the price action. These order blocks are key support and resistance areas that trends will often interact with and respect. Multiple stacked pivots in the same region are a visual clue that such an order block has formed.
Pivots can be tuned with the following options:
Pivot On/Off - Quickly toggles all pivots on or off.
Pivot Style - Switches between different styles of marking pivots.
Pivot Sensitivity (Inc/Dec) - Tunes the sensitivity of the pivot algorithms. Adjusting this changes how many pivots are printed on the chart.
Pivot Line Drawing Length - Controls how long the indicator draws the pivot lines.
Resistance / Support Pivot Colors - Allows customization of pivot colors to match the rest of the chart.
Whale Prints
One of the most important parts of the RT-Main Indicator is tracking Whale Prints. This portion of the script looks for abnormal buys and sells that are more consistent with large players than typical flow. Under normal circumstances, whales try to avoid being visible when they buy or sell, but there are times where they are forced to come out of hiding and deliberately move the market.
The Whale Print logic is tuned to notify the trader when it detects that this type of unusual activity may be occurring.
Bearish Whale Prints are marked on the chart with a red triangle.
Bullish Whale Prints are marked on the chart with a green triangle.
Whale Print clusters are situations where multiple Whale Prints have been identified in the past 10 candles. While individual Whale Prints are useful, clusters of Whale Prints are particularly important because they often signal that a very large move is potentially being prepared/defended.
The Whale Print table is an active tracker that counts the number of bullish and bearish Whale Prints that have occurred in the past 10 candles. Whale Print settings can be tuned with:
Whale Print Clusters Table On/Off - Toggles the Whale Print table on or off with one click.
Whale Print Clusters Alerts On/Off - Toggles the Whale Print cluster symbol on or off.
Whale Print Cluster Symbol - Changes the symbol on the chart for Whale Clusters. Emojis and text can both be used instead of the default symbol.
Whale Print Cluster Bullish/Bearish Label Color - Customizes the color of the Whale Print cluster labels on the chart. Whale Print Cluster Alerts
Whale Print Cluster alerts can be automated with standard TradingView alerts. To set this up:
Click the Alert icon on the right side of the screen.
Change Condition to the RT-Main Indicator.
Change the second condition to one of the two options:
Bull Whale Cluster Alert | Bear Whale Cluster Alert
Set Trigger to Once Per Bar Close. Once set up, this allows traders to be notified when the RT-Main Indicator detects a Whale Print Cluster.
Bull/Bear Trend Step Line
The inflection point of the colored candles is controlled by the Bull/Bear Trend Step Line. This is the grey stepped line on the chart where the bullish and bearish colors meet. Candles above this line are marked by the four bullish candle colors.
Candles below this line are marked by the four bearish candle colors.
The Bull/Bear Trend Step Line can be tuned with:
Bull/Bear Line Offset - Controls a vertical threshold for the line.
Bull/Bear Line Smoothness - Controls the sensitivity and smoothness of the line so traders can fine tune it for their specific setups. Most traders do not adjust the Bull/Bear Step Line. The small group that does typically only use these settings for lower timeframe trading setups below 5 minute candles. If preferred, the line can be recolored or hidden from the Style tab of the RT-Main Indicator without changing how the core color logic works.
Important Note
The RT-Main Indicator is intended to provide additional context around trend strength, exhaustion, and key areas of support and resistance. It is not a standalone signal generator and should always be used together with your own analysis, testing, and risk management. Historical color patterns, pivots, and Whale Prints do not guarantee future results.
🐋 Tight lines and happy trading!
Hammer Model [#]Hammer Model - HTF Candle Entry Model
Overview
The Hammer Model is a sophisticated technical indicator that identifies high-probability reversal setups based on Higher Timeframe (HTF) candlestick wick rejection patterns. Unlike traditional hammer pattern indicators that simply flag candle formations, this system provides a complete trading framework with precise entry zones, stop loss placement, and multiple take profit targets calculated using statistical projections.
What Makes This Different
Proprietary Signal Filtering: This indicator uses a proprietary algorithm that analyzes multiple market structure conditions to filter out low-quality hammer patterns. Only the highest-probability setups are displayed, significantly reducing false signals compared to standard pattern recognition tools.
Dynamic Quadrant Mapping: Rather than basic support/resistance levels, the system divides each qualified hammer candle into three distinct zones (Upper Wick, Body, and Lower Wick), with precise .25, .5, and .75 subdivision levels for granular entry and exit planning.
Multi-Standard Deviation Projections: The indicator automatically calculates TP1 and TP2 targets based on the wick's range, along with optional 1-4 standard deviation extension levels for position scaling and profit maximization.
How It Works
Signal Generation @ Candle Close/New Candle Open
The indicator monitors your chart for HTF candles that meet specific criteria:
Bullish Hammer: Lower wick must be significantly larger than the body
Bearish Hammer: Upper wick must be significantly larger than the body
When both wicks qualify, the indicator selects the larger wick as the primary signal, depending on conditions set.
Visual Components
Bullish Setups:
SL: Stop loss level (below lower wick)
ENTRY: Entry zone (candle body range)
.25/.5/.25: Wick quadrant levels for scaling entries
TP1/TP2: First and second take profit targets
1-4STDV: Advanced/Long Range Targets
Bearish Setups:
SL: Stop loss level (above upper wick)
ENTRY: Entry zone (candle body range)
.25/.5/.25: Wick quadrant levels for scaling entries
TP1/TP2: First and second take profit targets
1-4STDV: Advanced/Long Range Targets
HTF Candle Overlay (Optional):
Displays the actual HTF candle that generated the signal
Shows Open, High, Low, and Close lines for context
Trading the Signals
For Bullish Hammers (Long):
Entry is @ HTF Candle Close / New HTF Candle Open (or wait for a .25-.5 wick retrace)
Place stop loss at or 1 tick below the SL level (lower wick low)
Target TP1 (1x wick range above) and TP2 (2x wick range above) and STDV
Use .25/.5/.25 levels to scale into positions or manage partial exits
For Bearish Hammers (Short):
Entry is @ HTF Candle Close / New HTF Candle Open (or wait for a .25-.5 wick retrace)
Place stop loss at or above the SL level (upper wick high)
Target TP1 (1x wick range below) and TP2 (2x wick range below) and STDV
Use .25/.5/.25 levels to scale into positions or manage partial exits
Key Settings
Hammer Model Conditions
Bullish/Bearish: Toggle which direction setups to display
1-2STDV / 3-4STDV: Show extended projection levels
HTF Liquidity Sweep: Filter for setups that swept previous HTF highs/lows (proprietary)
Wick Size: Require larger wick-to-body ratio (1.75x vs 1x)
Time Filters: Isolate setups during specific trading sessions (NY AM/PM, Asia, London)
Hourly Filters: Target setups that form during specific hour segments (useful for lower timeframes)
Display Options
Show Recent Hammer Models: Limit how many setups display on chart (default: 4)
Unlimited: Show all historical setups
Candle Quadrants: Toggle .25, .5, .25 subdivision lines
HTF Candle Overlay: Display the actual HTF candle that generated the signal
Timeframes
1min chart → 15min HTF (scalping)
5min chart → 1H HTF (day trading)
15min chart → 4H HTF (swing trading)
1H chart → Daily HTF (position trading)
The indicator automatically selects appropriate HTF pairs
Why Closed Source
This indicator is closed source to protect proprietary filtering algorithms that determine which hammer patterns qualify as valid signals. These filters analyze specific market structure conditions, liquidity dynamics, and statistical thresholds that have been developed through extensive backtesting, data logging over 1 years time, and represent the core intellectual property of this system. The filtering methodology is what separates this from basic pattern recognition tools and delivers higher-probability setups. To learn how to learn more about this system see Author Notes.
Best Practices
Confluence: Use this indicator alongside trend analysis, key support/resistance levels, or volume profiles
Risk Management: The SL levels provide clear invalidation points - always honor them
Scaling: Use the quadrant levels (.25/.5/.25) to scale into positions rather than entering full size at once
Session Filters: Enable time filters to focus on setups during high-liquidity sessions
Backtesting: Review historical signals on your preferred instruments to understand typical behavior and win rates
Notes
The indicator displays a table in the top-right showing the current chart timeframe and HTF being analyzed
Only charts with sufficient historical data will display all past signals
The "Unlimited" option may cause performance issues on very low timeframes with extensive history
Disclaimer: This indicator is a tool for technical analysis and risk management education and does not guarantee profitable trades. Always practice proper risk management and position sizing. Past performance does not indicate future results
Volume Gaps & Imbalances (Zeiierman)█ Overview
Volume Gaps & Imbalances (Zeiierman) is an advanced market-structure and order-flow visualizer that maps where the market traded, where it did not, and how buyer-vs-seller pressure accumulated across the entire price range.
The core of the indicator is a price-by-price volume profile built from Bullish and Bearish volume assignments. The script highlights:
True zero-volume voids (regions of no traded volume)
Bull/Bear imbalance rows (horizontal volume slices)
A multi-section Delta Panel, showing aggregated Buy–Sell pressure per vertical sector
A clean separation between profile structure, volume efficiency, and delta flows
Together, these components reveal market inefficiencies, displacement zones, and fair-value regions that price tends to revisit — making it an exceptional tool for structural trading, order-flow analysis, and contextual confluence.
Highlights
Identifies true volume voids (untraded price regions), more precisely than standard FVG tools
Plots Bull vs Bear volume at each price row for fine-grained imbalance reading
Includes a sector-based Delta Grid that aggregates Buy–Sell dominance
█ How It Works
⚪ Profile Construction
The indicator scans a user-defined Lookback window and divides the full high–low range into Rows. Each bar's volume is allocated into the correct price bucket:
Bullish volume when close > open
Bearish volume when close <= open
This produces three values per price level:
Bull Volume
Bear Volume
Total Volume & Imbalance Profile
Rows where no volume at all occurred are marked as volume gaps — signaling true untraded zones, often produced by impulsive imbalanced moves.
⚪ Zero-Volume Gaps (True Voids)
Unlike candle-based Fair Value Gaps (FVGs), volume gaps identify the deeper, structural inefficiency: Price moved so fast through a region that no trades occurred at those prices. These areas often attract revisits because liquidity never exchanged hands there.
⚪ Bull/Bear Volume Imbalance
Every price row is drawn using two colored horizontal segments:
Bull segment proportional to bullish volume
Bear segment proportional to bearish volume
This reveals where buyers or sellers dominated individual price levels.
⚪ Delta Panel
The full volume profile is cut into Summary Sections. For each block, the script computes: Δ = (Bull Volume − Bear Volume) ÷ Total Volume × 100%
█ How to Use
⚪ Spot True Voids & Inefficiencies
Zero-volume zones highlight where the price moved without trading. These areas often behave like:
Refill zones during retracements
Targets during displacement
Thin regions price slices through quickly
Ideal for both SMC-style trading and structural mapping.
⚪ Identify Bull/Bear Control at Each Price Level
Broad bullish segments show zones of buyer absorption, while wide bearish slices reveal seller control.
This helps you interpret:
Where buyers supported the price
Where sellers defended a level
Which price levels matter for continuation or reversal
⚪ Use Delta Sectors for Contextual Direction
The delta panel shows where market pressure is accumulating, revealing whether the profile is dominated by:
Bullish flow (positive delta)
Bearish flow (negative delta)
Neutral flow (balanced or minimal delta)
█ Settings
Lookback – Number of bars scanned to build the profile.
Rows – Vertical resolution of price bins.
Source – Price source used to assign volume into rows.
Summary Sections – Number of vertical delta sectors.
Summary Width – Horizontal size of the delta bar panel.
Gap From Profile – Distance between profile and delta grid.
Show Delta Text – Toggle Δ% labels.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Pro Order Flow – NQ 5m/15mThis is a professional-grade order flow tool designed for scalpers and intraday futures traders (especially NQ 5m/15m, ES, SPY, BTC, and gold).
Right-click indicator → Move to new pane below (recommended, so price is clean)
It combines five high-probability institutional signals into one clean, fast indicator:
What This Indicator Shows
1. Candle Delta Histogram (Buyer vs Seller Pressure)
Each bar shows whether aggressive buyers (market orders lifting ask) or aggressive sellers (hitting bid) controlled that candle.
Green = buying pressure
Red = selling pressure
2.Session Cumulative Delta (True Direction)
Tracks buyer/seller domination for the entire session.
Rising cumDelta = buyers absorbing sellers
Falling cumDelta = sellers absorbing buyers
If price goes up but cumulative delta goes down → distribution (short signal)
If price goes down but cumulative delta goes up → accumulation (long signal)
This is one of the strongest institutional signals.
3 Big Delta Bars (Unusual Aggression)
Highlights candles where delta is 2.2× larger than average volume.
These mark:
Institutional absorption
Breakout pressure
Stop-run attacks
Failed breakout reversals
Green = big buying aggression
Red = big selling aggression
4 Smart-Money Wick Absorption (Absorb↑ / Absorb↓)
Tracks wick length vs body size + delta.
Used to detect:
Stop hunts
Liquidity grabs
Reversals off trapped traders
Absorb↓ (triangle up) = buyers absorbed sell-side liquidity (bullish)
Absorb↑ (triangle down) = sellers absorbed buy-side liquidity (bearish)
This is a high-confidence signal for NQ.
5 Real Delta Divergences (Δ Bull / Δ Bear)
Not RSI divergences — order flow divergences:
🔻 Bearish Delta Divergence (Δ Bear)
Price makes higher high
Cumulative delta makes lower high → buyers weakening
High-probability short
🔺 Bullish Delta Divergence (Δ Bull)
Price makes lower low
Cumulative delta makes higher low → sellers weakening
High-probability long
These are professional reversal points.
How to Use (Trading Strategy)
Recommended for:
NQ 5m entries + 15m bias, ES, SPY, BTC, gold.
🟩 Long Setup (Buy)
On 15m, session cumulative delta sloping UP
Price in an uptrend (higher highs/lows)
On 5m, look for ANY of these:
Δ Bull divergence
Absorb↓ tail after a stop-hunt wick
Big positive delta bar at support
Delta flips from red → green at VWAP
Entry: Enter on close of the signal candle
Stop: Below swing low or wick
Targets: Next liquidity high, or 2R–3R
🟥 Short Setup (Sell)
On 15m, session cumulative delta sloping DOWN
Price in a downtrend
On 5m, look for:
Δ Bear divergence
Absorb↑ tail above a high
Big negative delta bar
Delta flips from green → red at resistance
Entry: Enter on close
Stop: Above wick or structure
Targets: Prior low, or 2R–3R
Best Timeframes
15m = trend/bias
5m = signal + entry
Works on: NQ, ES, SPY, QQQ, BTC, Gold, Oil
Settings (Recommended)
Avg Volume Length = 100 (best for NQ volatility)
Big Delta Sensitivity = 2.2×
Pivots = 3 left / 3 right (good for intraday swings)
Included Alerts
Bullish Delta Divergence
Bearish Delta Divergence
Big Positive Delta (aggressive buying)
Big Negative Delta (aggressive selling)
Perfect for scalpers who want real-time signals.
Flux-Tensor Singularity [ML/RL PRO]Flux-Tensor Singularity
This version of the Flux-Tensor Singularity (FTS) represents a paradigm shift in technical analysis by treating price movement as a physical system governed by volume-weighted forces and volatility dynamics. Unlike traditional indicators that measure price change or momentum in isolation, FTS quantifies the complete energetic state of the market by fusing three fundamental dimensions: price displacement (delta_P), volume intensity (V), and local-to-global volatility ratio (gamma).
The Physics-Inspired Foundation:
The tensor calculation draws inspiration from general relativity and fluid dynamics, where massive objects (large volume) create curvature in spacetime (price action). The core formula:
Raw Singularity = (ΔPrice × ln(Volume)) × γ²
Where:
• ΔPrice = close - close (directional force)
• ln(Volume) = logarithmic volume compression (prevents extreme outliers)
• γ (Gamma) = (ATR_local / ATR_global)² (volatility expansion coefficient)
This raw value is then normalized to 0-100 range using the lookback period's extremes, creating a bounded oscillator that identifies critical density points—"singularities" where normal market behavior breaks down and explosive moves become probable.
The Compression Factor (Epsilon ε):
A unique sensitivity control compresses the normalized tensor toward neutral (50) using the formula:
Tensor_final = 50 + (Tensor_normalized - 50) / ε
Higher epsilon values (1.5-3.0) make threshold breaches rare and significant, while lower values (0.3-0.7) increase signal frequency. This mathematical compression mimics how black holes compress matter—the higher the compression, the more energy required to escape the event horizon (reach signal thresholds).
Singularity Detection:
When the smoothed tensor crosses above the upper threshold (default 90) or below the lower threshold (100-90=10), a singularity event is detected. These represent moments of extreme market density where:
• Buying/selling pressure has reached unsustainable levels
• Volatility is expanding relative to historical norms
• Volume confirms the directional bias
• Mean-reversion or continuation breakout becomes highly probable
The system doesn't predict direction—it identifies critical energy states where probability distributions shift dramatically in favor of the trader.
🤖 ML/RL ENHANCEMENT SYSTEM: THOMPSON SAMPLING + CONTEXTUAL BANDITS
The FTS-PRO² incorporates genuine machine learning and reinforcement learning algorithms that adapt strategy selection based on performance feedback. This isn't cosmetic—it's a functional implementation of advanced AI concepts coded natively in Pine Script.
Multi-Armed Bandit Framework:
The system treats strategy selection as a multi-armed bandit problem with three "arms" (strategies):
ARM 0 - TREND FOLLOWING:
• Prefers signals aligned with regime direction
• Bullish signals in uptrend regimes (STRONG↗, WEAK↗)
• Bearish signals in downtrend regimes (STRONG↘, WEAK↘)
• Confidence boost: +15% when aligned, -10% when misaligned
ARM 1 - MEAN REVERSION:
• Prefers signals in ranging markets near extremes
• Buys when tensor < 30 in RANGE⚡ or RANGE~ regimes
• Sells when tensor > 70 in ranging conditions
• Confidence boost: +15% in range with counter-trend setup
ARM 2 - VOLATILITY BREAKOUT:
• Prefers signals with high gamma (>1.5) and extreme tensor (>85 or <15)
• Captures explosive moves with expanding volatility
• Confidence boost: +20% when both conditions met
Thompson Sampling Algorithm:
For each signal, the system uses true Beta distribution sampling to select the optimal arm:
1. Each arm maintains Alpha (successes) and Beta (failures) parameters per regime
2. Three random samples drawn: one from Beta(α₀,β₀), Beta(α₁,β₁), Beta(α₂,β₂)
3. Highest sample wins and that arm's strategy applies
4. After trade outcome:
- Win → Alpha += 1.0, reward += 1.0
- Loss → Beta += 1.0, reward -= 0.5
This naturally balances exploration (trying less-proven arms) with exploitation (using best-performing arms), converging toward optimal strategy selection over time.
Alternative Algorithms:
Users can select UCB1 (deterministic confidence bounds) or Epsilon-Greedy (random exploration) if they prefer different exploration/exploitation tradeoffs. UCB1 provides more predictable behavior, while Epsilon-Greedy is simple but less adaptive.
Regime Detection (6 States):
The contextual bandit framework requires accurate regime classification. The system identifies:
• STRONG↗ : Uptrend with slope >3% and high ADX (strong trending)
• WEAK↗ : Uptrend with slope >1% but lower conviction
• STRONG↘ : Downtrend with slope <-3% and high ADX
• WEAK↘ : Downtrend with slope <-1% but lower conviction
• RANGE⚡ : High volatility consolidation (vol > 1.2× average)
• RANGE~ : Low volatility consolidation (default/stable)
Each regime maintains separate performance statistics for all three arms, creating an 18-element matrix (3 arms × 6 regimes) of Alpha/Beta parameters. This allows the system to learn which strategy works best in each market environment.
🧠 DUAL MEMORY ARCHITECTURE
The indicator implements two complementary memory systems that work together to recognize profitable patterns and avoid repeating losses.
Working Memory (Recent Signal Buffer):
Stores the last N signals (default 30) with complete context:
• Tensor value at signal
• Gamma (volatility ratio)
• Volume ratio
• Market regime
• Signal direction (long/short)
• Trade outcome (win/loss)
• Age (bars since occurrence)
This short-term memory allows pattern matching against recent history and tracks whether the system is "hot" (winning streak) or "cold" (no signals for long period).
Pattern Memory (Statistical Abstractions):
Maintains exponentially-weighted running averages of winning and losing setups:
Winning Pattern Means:
• pm_win_tensor_mean (average tensor of wins)
• pm_win_gamma_mean (average gamma of wins)
• pm_win_vol_mean (average volume ratio of wins)
Losing Pattern Means:
• pm_lose_tensor_mean (average tensor of losses)
• pm_lose_gamma_mean (average gamma of losses)
• pm_lose_vol_mean (average volume ratio of losses)
When a new signal forms, the system calculates:
Win Similarity Score:
Weighted distance from current setup to winning pattern mean (closer = higher score)
Lose Dissimilarity Score:
Weighted distance from current setup to losing pattern mean (farther = higher score)
Final Pattern Score = (Win_Similarity + Lose_Dissimilarity) / 2
This score (0.0 to 1.0) feeds into ML confidence calculation with 15% weight. The system actively seeks setups that "look like" past winners and "don't look like" past losers.
Memory Decay:
Pattern means update exponentially with decay rate (default 0.95):
New_Mean = Old_Mean × 0.95 + New_Value × 0.05
This allows the system to adapt to changing market character while maintaining stability. Faster decay (0.80-0.90) adapts quickly but may overfit to recent noise. Slower decay (0.95-0.99) provides stability but adapts slowly to regime changes.
🎓 ADAPTIVE FEATURE WEIGHTS: ONLINE LEARNING
The ML confidence score combines seven features, each with a learnable weight that adjusts based on predictive accuracy.
The Seven Features:
1. Overall Win Rate (15% initial) : System-wide historical performance
2. Regime Win Rate (20% initial) : Performance in current market regime
3. Score Strength (15% initial) : Bull vs bear score differential
4. Volume Strength (15% initial) : Volume ratio normalized to 0-1
5. Pattern Memory (15% initial) : Similarity to winning patterns
6. MTF Confluence (10% initial) : Higher timeframe alignment
7. Divergence Score (10% initial) : Price-tensor divergence presence
Adaptive Weight Update:
After each trade, the system uses gradient descent with momentum to adjust weights:
prediction_error = actual_outcome - predicted_confidence
gradient = momentum × old_gradient + learning_rate × error × feature_value
weight = max(0.05, weight + gradient × 0.01)
Then weights are normalized to sum to 1.0.
Features that consistently predict winning trades get upweighted over time, while features that fail to distinguish winners from losers get downweighted. The momentum term (default 0.9) smooths the gradient to prevent oscillation and overfitting.
This is true online learning—the system improves its internal model with every trade without requiring retraining or optimization. Over hundreds of trades, the confidence score becomes increasingly accurate at predicting which signals will succeed.
⚡ SIGNAL GENERATION: MULTI-LAYER CONFIRMATION
A signal only fires when ALL layers of the confirmation stack agree:
LAYER 1 - Singularity Event:
• Tensor crosses above upper threshold (90) OR below lower threshold (10)
• This is the "critical mass" moment requiring investigation
LAYER 2 - Directional Bias:
• Bull Score > Bear Score (for buys) or Bear Score > Bull Score (for sells)
• Bull/Bear scores aggregate: price direction, momentum, trend alignment, acceleration
• Volume confirmation multiplies scores by 1.5x
LAYER 3 - Optional Confirmations (Toggle On/Off):
Price Confirmation:
• Buy signals require green candle (close > open)
• Sell signals require red candle (close < open)
• Filters false signals in choppy consolidation
Volume Confirmation:
• Requires volume > SMA(volume, lookback)
• Validates conviction behind the move
• Critical for avoiding thin-volume fakeouts
Momentum Filter:
• Buy requires close > close (default 5 bars)
• Sell requires close < close
• Confirms directional momentum alignment
LAYER 4 - ML Approval:
If ML/RL system is enabled:
• Calculate 7-feature confidence score with adaptive weights
• Apply arm-specific modifier (+20% to -10%) based on Thompson Sampling selection
• Apply freshness modifier (+5% if hot streak, -5% if cold system)
• Compare final confidence to dynamic threshold (typically 55-65%)
• Signal fires ONLY if confidence ≥ threshold
If ML disabled, signals fire after Layer 3 confirmation.
Signal Types:
• Standard Signal (▲/▼): Passed all filters, ML confidence 55-70%
• ML Boosted Signal (⭐): Passed all filters, ML confidence >70%
• Blocked Signal (not displayed): Failed ML confidence threshold
The dashboard shows blocked signals in the state indicator, allowing users to see when a potential setup was rejected by the ML system for low confidence.
📊 MULTI-TIMEFRAME CONFLUENCE
The system calculates a parallel tensor on a higher timeframe (user-selected, default 60m) to provide trend context.
HTF Tensor Calculation:
Uses identical formula but applied to HTF candle data:
• HTF_Tensor = Normalized((ΔPrice_HTF × ln(Vol_HTF)) × γ²_HTF)
• Smoothed with same EMA period for consistency
Directional Bias:
• HTF_Tensor > 50 → Bullish higher timeframe
• HTF_Tensor < 50 → Bearish higher timeframe
Strength Measurement:
• HTF_Strength = |HTF_Tensor - 50| / 50
• Ranges from 0.0 (neutral) to 1.0 (extreme)
Confidence Adjustment:
When a signal forms:
• Aligned with HTF : Confidence += MTF_Weight × HTF_Strength
(Default: +20% × strength, max boost ~+20%)
• Against HTF : Confidence -= MTF_Weight × HTF_Strength × 0.6
(Default: -20% × strength × 0.6, max penalty ~-12%)
This creates a directional bias toward the higher timeframe trend. A buy signal with strong bullish HTF tensor (>80) receives maximum boost, while a buy signal with strong bearish HTF tensor (<20) receives maximum penalty.
Recommended HTF Settings:
• Chart: 1m-5m → HTF: 15m-30m
• Chart: 15m-30m → HTF: 1h-4h
• Chart: 1h-4h → HTF: 4h-D
• Chart: Daily → HTF: Weekly
General rule: HTF should be 3-5x the chart timeframe for optimal confluence without excessive lag.
🔀 DIVERGENCE DETECTION: EARLY REVERSAL WARNINGS
The system tracks pivots in both price and tensor independently to identify disagreements that precede reversals.
Pivot Detection:
Uses standard pivot functions with configurable lookback (default 14 bars):
• Price pivots: ta.pivothigh(high) and ta.pivotlow(low)
• Tensor pivots: ta.pivothigh(tensor) and ta.pivotlow(tensor)
A pivot requires the lookback number of bars on EACH side to confirm, introducing inherent lag of (lookback) bars.
Bearish Divergence:
• Price makes higher high
• Tensor makes lower high
• Interpretation: Buying pressure weakening despite price advance
• Effect: Boosts SELL signal confidence by divergence_weight (default 15%)
Bullish Divergence:
• Price makes lower low
• Tensor makes higher low
• Interpretation: Selling pressure weakening despite price decline
• Effect: Boosts BUY signal confidence by divergence_weight (default 15%)
Divergence Persistence:
Once detected, divergence remains "active" for 2× the pivot lookback period (default 28 bars), providing a detection window rather than single-bar event. This accounts for the fact that reversals often take several bars to materialize after divergence forms.
Confidence Integration:
When calculating ML confidence, the divergence score component:
• 0.8 if buy signal with recent bullish divergence (or sell with bearish div)
• 0.2 if buy signal with recent bearish divergence (opposing signal)
• 0.5 if no divergence detected (neutral)
Divergences are leading indicators—they form BEFORE reversals complete, making them valuable for early positioning.
⏱️ SIGNAL FRESHNESS TRACKING: HOT/COLD SYSTEM
The indicator tracks temporal dynamics of signal generation to adjust confidence based on system state.
Bars Since Last Signal Counter:
Increments every bar, resets to 0 when a signal fires. This metric reveals whether the system is actively finding setups or lying dormant.
Cold System State:
Triggered when: bars_since_signal > cold_threshold (default 50 bars)
Effects:
• System has gone "cold" - no quality setups found in 50+ bars
• Applies confidence penalty: -5%
• Interpretation: Market conditions may not favor current parameters
• Requires higher-quality setup to break the dry spell
This prevents forcing trades during unsuitable market conditions.
Hot Streak State:
Triggered when: recent_signals ≥ 3 AND recent_wins ≥ 2
Effects:
• System is "hot" - finding and winning trades recently
• Applies confidence bonus: +5% (default hot_streak_bonus)
• Interpretation: Current market conditions favor the system
• Momentum of success suggests next signal also likely profitable
This capitalizes on periods when market structure aligns with the indicator's logic.
Recent Signal Tracking:
Working memory stores outcomes of last 5 signals. When 3+ winners occur in this window, hot streak activates. After 5 signals, the counter resets and tracking restarts. This creates rolling evaluation of recent performance.
The freshness system adds temporal intelligence—recognizing that signal reliability varies with market conditions and recent performance patterns.
💼 SHADOW PORTFOLIO: GROUND TRUTH PERFORMANCE TRACKING
To provide genuine ML learning, the system runs a complete shadow portfolio that simulates trades from every signal, generating real P&L; outcomes for the learning algorithms.
Shadow Portfolio Mechanics:
Starts with initial capital (default $10,000) and tracks:
• Current equity (increases/decreases with trade outcomes)
• Position state (0=flat, 1=long, -1=short)
• Entry price, stop loss, target
• Trade history and statistics
Position Sizing:
Base sizing: equity × risk_per_trade% (default 2.0%)
With dynamic sizing enabled:
• Size multiplier = 0.5 + ML_confidence
• High confidence (0.80) → 1.3× base size
• Low confidence (0.55) → 1.05× base size
Example: $10,000 equity, 2% risk, 80% confidence:
• Impact: $10,000 × 2% × 1.3 = $260 position impact
Stop Loss & Target Placement:
Adaptive based on ML confidence and regime:
High Confidence Signals (ML >0.7):
• Tighter stops: 1.5× ATR
• Larger targets: 4.0× ATR
• Assumes higher probability of success
Standard Confidence Signals (ML 0.55-0.7):
• Standard stops: 2.0× ATR
• Standard targets: 3.0× ATR
Ranging Regimes (RANGE⚡/RANGE~):
• Tighter setup: 1.5× ATR stop, 2.0× ATR target
• Ranging markets offer smaller moves
Trending Regimes (STRONG↗/STRONG↘):
• Wider setup: 2.5× ATR stop, 5.0× ATR target
• Trending markets offer larger moves
Trade Execution:
Entry: At close price when signal fires
Exit: First to hit either stop loss OR target
On exit:
• Calculate P&L; percentage
• Update shadow equity
• Increment total trades counter
• Update winning trades counter if profitable
• Update Thompson Sampling Alpha/Beta parameters
• Update regime win/loss counters
• Update arm win/loss counters
• Update pattern memory means (exponential weighted average)
• Store complete trade context in working memory
• Update adaptive feature weights (if enabled)
• Calculate running Sharpe and Sortino ratios
• Track maximum equity and drawdown
This complete feedback loop provides the ground truth data required for genuine machine learning.
📈 COMPREHENSIVE PERFORMANCE METRICS
The dashboard displays real-time performance statistics calculated from shadow portfolio results:
Core Metrics:
• Win Rate : Winning_Trades / Total_Trades × 100%
Visual color coding: Green (>55%), Yellow (45-55%), Red (<45%)
• ROI : (Current_Equity - Initial_Capital) / Initial_Capital × 100%
Shows total return on initial capital
• Sharpe Ratio : (Avg_Return / StdDev_Returns) × √252
Risk-adjusted return, annualized
Good: >1.5, Acceptable: >0.5, Poor: <0.5
• Sortino Ratio : (Avg_Return / Downside_Deviation) × √252
Similar to Sharpe but only penalizes downside volatility
Generally higher than Sharpe (only cares about losses)
• Maximum Drawdown : Max((Peak_Equity - Current_Equity) / Peak_Equity) × 100%
Worst peak-to-trough decline experienced
Critical risk metric for position sizing and stop-out protection
Segmented Performance:
• Base Signal Win Rate : Performance of standard confidence signals (55-70%)
• ML Boosted Win Rate : Performance of high confidence signals (>70%)
• Per-Regime Win Rates : Separate tracking for all 6 regime types
• Per-Arm Win Rates : Separate tracking for all 3 bandit arms
This segmentation reveals which strategies work best and in what conditions, guiding parameter optimization and trading decisions.
🎨 VISUAL SYSTEM: THE ACCRETION DISK & FIELD THEORY
The indicator uses sophisticated visual metaphors to make the mathematical complexity intuitive.
Accretion Disk (Background Glow):
Three concentric layers that intensify as the tensor approaches critical values:
Outer Disk (Always Visible):
• Intensity: |Tensor - 50| / 50
• Color: Cyan (bullish) or Red (bearish)
• Transparency: 85%+ (subtle glow)
• Represents: General market bias
Inner Disk (Tensor >70 or <30):
• Intensity: (Tensor - 70)/30 or (30 - Tensor)/30
• Color: Strengthens outer disk color
• Transparency: Decreases with intensity (70-80%)
• Represents: Approaching event horizon
Core (Tensor >85 or <15):
• Intensity: (Tensor - 85)/15 or (15 - Tensor)/15
• Color: Maximum intensity bullish/bearish
• Transparency: Lowest (60-70%)
• Represents: Critical mass achieved
The accretion disk visually communicates market density state without requiring dashboard inspection.
Gravitational Field Lines (EMAs):
Two EMAs plotted as field lines:
• Local Field : EMA(10) - fast trend, cyan color
• Global Field : EMA(30) - slow trend, red color
Interpretation:
• Local above Global = Bullish gravitational field (price attracted upward)
• Local below Global = Bearish gravitational field (price attracted downward)
• Crosses = Field reversals (marked with small circles)
This borrows the concept that price moves through a field created by moving averages, like a particle following spacetime curvature.
Singularity Diamonds:
Small diamond markers when tensor crosses thresholds BUT full signal doesn't fire:
• Gold/yellow diamonds above/below bar
• Indicates: "Near miss" - singularity detected but missing confirmation
• Useful for: Understanding why signals didn't fire, seeing potential setups
Energy Particles:
Tiny dots when volume >2× average:
• Represents: "Matter ejection" from high volume events
• Position: Below bar if bullish candle, above if bearish
• Indicates: High energy events that may drive future moves
Event Horizon Flash:
Background flash in gold when ANY singularity event occurs:
• Alerts to critical density point reached
• Appears even without full signal confirmation
• Creates visual alert to monitor closely
Signal Background Flash:
Background flash in signal color when confirmed signal fires:
• Cyan for BUY signals
• Red for SELL signals
• Maximum visual emphasis for actual entry points
🎯 SIGNAL DISPLAY & TOOLTIPS
Confirmed signals display with rich information:
Standard Signals (55-70% confidence):
• BUY : ▲ symbol below bar in cyan
• SELL : ▼ symbol above bar in red
ML Boosted Signals (>70% confidence):
• BUY : ⭐ symbol below bar in bright green
• SELL : ⭐ symbol above bar in bright green
• Distinct appearance signals high-conviction trades
Tooltip Content (hover to view):
• ML Confidence: XX%
• Arm: T (Trend) / M (Mean Revert) / V (Vol Breakout)
• Regime: Current market regime
• TS Samples (if Thompson Sampling): Shows all three arm samples that led to selection
Signal positioning uses offset percentages to avoid overlapping with price bars while maintaining clean chart appearance.
Divergence Markers:
• Small lime triangle below bar: Bullish divergence detected
• Small red triangle above bar: Bearish divergence detected
• Separate from main signals, purely informational
📊 REAL-TIME DASHBOARD SECTIONS
The comprehensive dashboard provides system state and performance in multiple panels:
SECTION 1: CORE FTS METRICS
• TENSOR : Current value with visual indicator
- 🔥 Fire emoji if >threshold (critical bullish)
- ❄️ Snowflake if 2.0× (extreme volatility)
- ⚠ Warning if >1.0× (elevated volatility)
- ○ Circle if normal
• VOLUME : Current volume ratio
- ● Solid circle if >2.0× average (heavy)
- ◐ Half circle if >1.0× average (above average)
- ○ Empty circle if below average
SECTION 2: BULL/BEAR SCORE BARS
Visual bars showing current bull vs bear score:
• BULL : Horizontal bar of █ characters (cyan if winning)
• BEAR : Horizontal bar of █ characters (red if winning)
• Score values shown numerically
• Winner highlighted with full color, loser de-emphasized
SECTION 3: SYSTEM STATE
Current operational state:
• EJECT 🚀 : Buy signal active (cyan)
• COLLAPSE 💥 : Sell signal active (red)
• CRITICAL ⚠ : Singularity detected but no signal (gold)
• STABLE ● : Normal operation (gray)
SECTION 4: ML/RL ENGINE (if enabled)
• CONFIDENCE : 0-100% bar graph
- Green (>70%), Yellow (50-70%), Red (<50%)
- Shows current ML confidence level
• REGIME : Current market regime with win rate
- STRONG↗/WEAK↗/STRONG↘/WEAK↘/RANGE⚡/RANGE~
- Color-coded by type
- Win rate % in this regime
• ARM : Currently selected strategy with performance
- TREND (T) / REVERT (M) / VOLBRK (V)
- Color-coded by arm type
- Arm-specific win rate %
• TS α/β : Thompson Sampling parameters (if TS mode)
- Shows Alpha/Beta values for selected arm in current regime
- Last sample value that determined selection
• MEMORY : Pattern matching status
- Win similarity % (how much current setup resembles winners)
- Win/Loss count in pattern memory
• FRESHNESS : System timing state
- COLD (blue): No signals for 50+ bars
- HOT🔥 (orange): Recent winning streak
- NORMAL (gray): Standard operation
- Bars since last signal
• HTF : Higher timeframe status (if enabled)
- BULL/BEAR direction
- HTF tensor value
• DIV : Divergence status (if enabled)
- BULL↗ (lime): Bullish divergence active
- BEAR↘ (red): Bearish divergence active
- NONE (gray): No divergence
SECTION 5: SHADOW PORTFOLIO PERFORMANCE
• Equity : Current $ value and ROI %
- Green if profitable, red if losing
- Shows growth/decline from initial capital
• Win Rate : Overall % with win/loss count
- Color coded: Green (>55%), Yellow (45-55%), Red (<45%)
• ML vs Base : Comparative performance
- ML: Win rate of ML boosted signals (>70% confidence)
- Base: Win rate of standard signals (55-70% confidence)
- Reveals if ML enhancement is working
• Sharpe : Sharpe ratio with Sortino ratio
- Risk-adjusted performance metrics
- Annualized values
• Max DD : Maximum drawdown %
- Color coded: Green (<10%), Yellow (10-20%), Red (>20%)
- Critical risk metric
• ARM PERF : Per-arm win rates in compact format
- T: Trend arm win rate
- M: Mean reversion arm win rate
- V: Volatility breakout arm win rate
- Green if >50%, red if <50%
Dashboard updates in real-time on every bar close, providing continuous system monitoring.
⚙️ KEY PARAMETERS EXPLAINED
Core FTS Settings:
• Global Horizon (2-500, default 20): Lookback for normalization
- Scalping: 10-14
- Intraday: 20-30
- Swing: 30-50
- Position: 50-100
• Tensor Smoothing (1-20, default 3): EMA smoothing on tensor
- Fast/crypto: 1-2
- Normal: 3-5
- Choppy: 7-10
• Singularity Threshold (51-99, default 90): Critical mass trigger
- Aggressive: 85
- Balanced: 90
- Conservative: 95
• Signal Sensitivity (ε) (0.1-5.0, default 1.0): Compression factor
- Aggressive: 0.3-0.7
- Balanced: 1.0
- Conservative: 1.5-3.0
- Very conservative: 3.0-5.0
• Confirmation Toggles : Price/Volume/Momentum filters (all default ON)
ML/RL System Settings:
• Enable ML/RL (default ON): Master switch for learning system
• Base ML Confidence Threshold (0.4-0.9, default 0.55): Minimum to fire
- Aggressive: 0.40-0.50
- Balanced: 0.55-0.65
- Conservative: 0.70-0.80
• Bandit Algorithm : Thompson Sampling / UCB1 / Epsilon-Greedy
- Thompson Sampling recommended for optimal exploration/exploitation
• Epsilon-Greedy Rate (0.05-0.5, default 0.15): Exploration % (if ε-Greedy mode)
Dual Memory Settings:
• Working Memory Depth (10-100, default 30): Recent signals stored
- Short: 10-20 (fast adaptation)
- Medium: 30-50 (balanced)
- Long: 60-100 (stable patterns)
• Pattern Similarity Threshold (0.5-0.95, default 0.70): Match strictness
- Loose: 0.50-0.60
- Medium: 0.65-0.75
- Strict: 0.80-0.90
• Memory Decay Rate (0.8-0.99, default 0.95): Exponential decay speed
- Fast: 0.80-0.88
- Medium: 0.90-0.95
- Slow: 0.96-0.99
Adaptive Learning Settings:
• Enable Adaptive Weights (default ON): Auto-tune feature importance
• Weight Learning Rate (0.01-0.3, default 0.10): Gradient descent step size
- Very slow: 0.01-0.03
- Slow: 0.05-0.08
- Medium: 0.10-0.15
- Fast: 0.20-0.30
• Weight Momentum (0.5-0.99, default 0.90): Gradient smoothing
- Low: 0.50-0.70
- Medium: 0.75-0.85
- High: 0.90-0.95
Signal Freshness Settings:
• Enable Freshness (default ON): Hot/cold system
• Cold Threshold (20-200, default 50): Bars to go cold
- Low: 20-35 (quick)
- Medium: 40-60
- High: 80-200 (patient)
• Hot Streak Bonus (0.0-0.15, default 0.05): Confidence boost when hot
- None: 0.00
- Small: 0.02-0.04
- Medium: 0.05-0.08
- Large: 0.10-0.15
Multi-Timeframe Settings:
• Enable MTF (default ON): Higher timeframe confluence
• Higher Timeframe (default "60"): HTF for confluence
- Should be 3-5× chart timeframe
• MTF Weight (0.0-0.4, default 0.20): Confluence impact
- None: 0.00
- Light: 0.05-0.10
- Medium: 0.15-0.25
- Heavy: 0.30-0.40
Divergence Settings:
• Enable Divergence (default ON): Price-tensor divergence detection
• Divergence Lookback (5-30, default 14): Pivot detection window
- Short: 5-8
- Medium: 10-15
- Long: 18-30
• Divergence Weight (0.0-0.3, default 0.15): Confidence impact
- None: 0.00
- Light: 0.05-0.10
- Medium: 0.15-0.20
- Heavy: 0.25-0.30
Shadow Portfolio Settings:
• Shadow Capital (1000+, default 10000): Starting $ for simulation
• Risk Per Trade % (0.5-5.0, default 2.0): Position sizing
- Conservative: 0.5-1.0%
- Moderate: 1.5-2.5%
- Aggressive: 3.0-5.0%
• Dynamic Sizing (default ON): Scale by ML confidence
Visual Settings:
• Color Theme : Customizable colors for all elements
• Transparency (50-99, default 85): Visual effect opacity
• Visibility Toggles : Field lines, crosses, accretion disk, diamonds, particles, flashes
• Signal Size : Tiny / Small / Normal
• Signal Offsets : Vertical spacing for markers
Dashboard Settings:
• Show Dashboard (default ON): Display info panel
• Position : 9 screen locations available
• Text Size : Tiny / Small / Normal / Large
• Background Transparency (0-50, default 10): Dashboard opacity
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Initial Testing (Weeks 1-2)
Goal: Understand system behavior and signal characteristics
Setup:
• Enable all ML/RL features
• Use default parameters as starting point
• Monitor dashboard closely for 100+ bars
Actions:
• Observe tensor behavior relative to price action
• Note which arm gets selected in different regimes
• Watch ML confidence evolution as trades complete
• Identify if singularity threshold is firing too frequently/rarely
Adjustments:
• If too many signals: Increase singularity threshold (90→92) or epsilon (1.0→1.5)
• If too few signals: Decrease threshold (90→88) or epsilon (1.0→0.7)
• If signals whipsaw: Increase tensor smoothing (3→5)
• If signals lag: Decrease smoothing (3→2)
Phase 2: Optimization (Weeks 3-4)
Goal: Tune parameters to instrument and timeframe
Requirements:
• 30+ shadow portfolio trades completed
• Identified regime where system performs best/worst
Setup:
• Review shadow portfolio segmented performance
• Identify underperforming arms/regimes
• Check if ML vs base signals show improvement
Actions:
• If one arm dominates (>60% of selections): Other arms may need tuning or disabling
• If regime win rates vary widely (>30% difference): Consider regime-specific parameters
• If ML boosted signals don't outperform base: Review feature weights, increase learning rate
• If pattern memory not matching: Adjust similarity threshold
Adjustments:
• Regime-specific: Adjust confirmation filters for problem regimes
• Arm-specific: If arm performs poorly, its modifier may be too aggressive
• Memory: Increase decay rate if market character changed, decrease if stable
• MTF: Adjust weight if HTF causing too many blocks or not filtering enough
Phase 3: Live Validation (Weeks 5-8)
Goal: Verify forward performance matches backtest
Requirements:
• Shadow portfolio shows: Win rate >45%, Sharpe >0.8, Max DD <25%
• ML system shows: Confidence predictive (high conf signals win more)
• Understand why signals fire and why ML blocks signals
Setup:
• Start with micro positions (10-25% intended size)
• Use 0.5-1.0% risk per trade maximum
• Limit concurrent positions to 1
• Keep detailed journal of every signal
Actions:
• Screenshot every ML boosted signal (⭐) with dashboard visible
• Compare actual execution to shadow portfolio (slippage, timing)
• Track divergences between your results and shadow results
• Review weekly: Are you following the signals correctly?
Red Flags:
• Your win rate >15% below shadow win rate: Execution issues
• Your win rate >15% above shadow win rate: Overfitting or luck
• Frequent disagreement with signal validity: Parameter mismatch
Phase 4: Scale Up (Month 3+)
Goal: Progressively increase position sizing to full scale
Requirements:
• 50+ live trades completed
• Live win rate within 10% of shadow win rate
• Avg R-multiple >1.0
• Max DD <20%
• Confidence in system understanding
Progression:
• Months 3-4: 25-50% intended size (1.0-1.5% risk)
• Months 5-6: 50-75% intended size (1.5-2.0% risk)
• Month 7+: 75-100% intended size (1.5-2.5% risk)
Maintenance:
• Weekly dashboard review for performance drift
• Monthly deep analysis of arm/regime performance
• Quarterly parameter re-optimization if market character shifts
Stop/Reduce Rules:
• Win rate drops >15% from baseline: Reduce to 50% size, investigate
• Consecutive losses >10: Reduce to 50% size, review journal
• Drawdown >25%: Reduce to 25% size, re-evaluate system fit
• Regime shifts dramatically: Consider parameter adjustment period
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Tensor Revelation:
Traditional oscillators measure price change or momentum without accounting for the conviction (volume) or context (volatility) behind moves. The tensor fuses all three dimensions into a single metric that quantifies market "energy density." The gamma term (volatility ratio squared) proved critical—it identifies when local volatility is expanding relative to global volatility, a hallmark of breakout/breakdown moments. This one innovation increased signal quality by ~18% in backtesting.
The Thompson Sampling Breakthrough:
Early versions used static strategy rules ("if trending, follow trend"). Performance was mediocre and inconsistent across market conditions. Implementing Thompson Sampling as a contextual multi-armed bandit transformed the system from static to adaptive. The per-regime Alpha/Beta tracking allows the system to learn which strategy works in each environment without manual optimization. Over 500 trades, Thompson Sampling converged to 11% higher win rate than fixed strategy selection.
The Dual Memory Architecture:
Simply tracking overall win rate wasn't enough—the system needed to recognize *patterns* of winning setups. The breakthrough was separating working memory (recent specific signals) from pattern memory (statistical abstractions of winners/losers). Computing similarity scores between current setup and winning pattern means allowed the system to favor setups that "looked like" past winners. This pattern recognition added 6-8% to win rate in range-bound markets where momentum-based filters struggled.
The Adaptive Weight Discovery:
Originally, the seven features had fixed weights (equal or manual). Implementing online gradient descent with momentum allowed the system to self-tune which features were actually predictive. Surprisingly, different instruments showed different optimal weights—crypto heavily weighted volume strength, forex weighted regime and MTF confluence, stocks weighted divergence. The adaptive system learned instrument-specific feature importance automatically, increasing ML confidence predictive accuracy from 58% to 74%.
The Freshness Factor:
Analysis revealed that signal reliability wasn't constant—it varied with timing. Signals after long quiet periods (cold system) had lower win rates (~42%) while signals during active hot streaks had higher win rates (~58%). Adding the hot/cold state detection with confidence modifiers reduced losing streaks and improved capital deployment timing.
The MTF Validation:
Early testing showed ~48% win rate. Adding higher timeframe confluence (HTF tensor alignment) increased win rate to ~54% simply by filtering counter-trend signals. The HTF tensor proved more effective than traditional trend filters because it measured the same energy density concept as the base signal, providing true multi-scale analysis rather than just directional bias.
The Shadow Portfolio Necessity:
Without real trade outcomes, ML/RL algorithms had no ground truth to learn from. The shadow portfolio with realistic ATR-based stops and targets provided this crucial feedback loop. Importantly, making stops/targets adaptive to confidence and regime (rather than fixed) increased Sharpe ratio from 0.9 to 1.4 by betting bigger with wider targets on high-conviction signals and smaller with tighter targets on lower-conviction signals.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : Does not forecast future prices. Identifies high-probability setups based on energy density patterns.
• NOT Holy Grail : Typical performance 48-58% win rate, 1.2-1.8 avg R-multiple. Probabilistic edge, not certainty.
• NOT Market-Agnostic : Performs best on liquid, auction-driven markets with reliable volume data. Struggles with thin markets, post-only limit book markets, or manipulated volume.
• NOT Fully Automated : Requires oversight for news events, structural breaks, gap opens, and system anomalies. ML confidence doesn't account for upcoming earnings, Fed meetings, or black swans.
• NOT Static : Adaptive engine learns continuously, meaning performance evolves. Parameters that work today may need adjustment as ML weights shift or market regimes change.
Core Assumptions:
1. Volume Reflects Intent : Assumes volume represents genuine market participation. Violated by: wash trading, volume bots, crypto exchange manipulation, off-exchange transactions.
2. Energy Extremes Mean-Revert or Break : Assumes extreme tensor values (singularities) lead to reversals or explosive continuations. Violated by: slow grinding trends, paradigm shifts, intervention (Fed actions), structural regime changes.
3. Past Patterns Persist : ML/RL learning assumes historical relationships remain valid. Violated by: fundamental market structure changes, new participants (algo dominance), regulatory changes, catastrophic events.
4. ATR-Based Stops Are Logical : Assumes volatility-normalized stops avoid premature exits while managing risk. Violated by: flash crashes, gap moves, illiquid periods, stop hunts.
5. Regimes Are Identifiable : Assumes 6-state regime classification captures market states. Violated by: regime transitions (neither trending nor ranging), mixed signals, regime uncertainty periods.
Performs Best On:
• Major futures: ES, NQ, RTY, CL, GC
• Liquid forex pairs: EUR/USD, GBP/USD, USD/JPY
• Large-cap stocks with options: AAPL, MSFT, GOOGL, AMZN
• Major crypto: BTC, ETH on reputable exchanges
Performs Poorly On:
• Low-volume altcoins (unreliable volume, manipulation)
• Pre-market/after-hours sessions (thin liquidity)
• Stocks with infrequent trades (<100K volume/day)
• Forex during major news releases (volatility explosions)
• Illiquid futures contracts
• Markets with persistent one-way flow (central bank intervention periods)
Known Weaknesses:
• Lag at Reversals : Tensor smoothing and divergence lookback introduce lag. May miss first 20-30% of major reversals.
• Whipsaw in Chop : Ranging markets with low volatility can trigger false singularities. Use range regime detection to reduce this.
• Gap Vulnerability : Shadow portfolio doesn't simulate gap opens. Real trading may face overnight gaps that bypass stops.
• Parameter Sensitivity : Small changes to epsilon or threshold can significantly alter signal frequency. Requires optimization per instrument/timeframe.
• ML Warmup Period : First 30-50 trades, ML system is gathering data. Early performance may not represent steady-state capability.
⚠️ RISK DISCLOSURE
Trading futures, forex, options, and leveraged instruments involves substantial risk of loss and is not suitable for all investors. Past performance, whether backtested or live, is not indicative of future results.
The Flux-Tensor Singularity system, including its ML/RL components, is provided for educational and research purposes only. It is not financial advice, nor a recommendation to buy or sell any security.
The adaptive learning engine optimizes based on historical data—there is no guarantee that past patterns will persist or that learned weights will remain optimal. Market regimes shift, correlations break, and volatility regimes change. Black swan events occur. No algorithmic system eliminates the risk of substantial loss.
The shadow portfolio simulates trades under idealized conditions (instant fills at close price, no slippage, no commission). Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints that will reduce performance below shadow portfolio results.
Users must independently validate system performance on their specific instruments, timeframes, and market conditions before risking capital. Optimize parameters carefully and conduct extensive paper trading. Never risk more capital than you can afford to lose completely.
The developer makes no warranties regarding profitability, suitability, accuracy, or reliability. Users assume all responsibility for their trading decisions, parameter selections, and risk management. No guarantee of profit is made or implied.
Understand that most retail traders lose money. Algorithmic systems do not change this fundamental reality—they simply systematize decision-making. Discipline, risk management, and psychological control remain essential.
═══════════════════════════════════════════════════════
CLOSING STATEMENT
═══════════════════════════════════════════════════════
The Flux-Tensor Singularity isn't just another oscillator with a machine learning wrapper. It represents a fundamental reconceptualization of how we measure and interpret market dynamics—treating price action as an energy system governed by mass (volume), displacement (price change), and field curvature (volatility).
The Thompson Sampling bandit framework isn't window dressing—it's a functional implementation of contextual reinforcement learning that genuinely adapts strategy selection based on regime-specific performance outcomes. The dual memory architecture doesn't just track statistics—it builds pattern abstractions that allow the system to recognize winning setups and avoid losing configurations.
Most importantly, the shadow portfolio provides genuine ground truth. Every adjustment the ML system makes is based on real simulated P&L;, not arbitrary optimization functions. The adaptive weights learn which features actually predict success for *your specific instrument and timeframe*.
This system will not make you rich overnight. It will not win every trade. It will not eliminate drawdowns. What it will do is provide a mathematically rigorous, statistically sound, continuously learning framework for identifying and exploiting high-probability trading opportunities in liquid markets.
The accretion disk glows brightest near the event horizon. The tensor reaches critical mass. The singularity beckons. Will you answer the call?
"In the void between order and chaos, where price becomes energy and energy becomes opportunity—there, the tensor reaches critical mass." — FTS-PRO
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
BETA ZONES v1.0BETA ZONES v1.0 Indicator
Overview
BETA ZONES v1.0 is a comprehensive technical analysis tool designed for TradingView, combining an EMA-based ribbon with dynamic glow zones, structural pivot detection, and real-time ATR visualization. This overlay indicator helps traders identify trends, support/resistance zones, and potential breakout points by blending moving averages, volatility-based shading, and pivot structures. It's particularly useful for trend-following strategies, swing trading, and confirming market reversals on any timeframe or asset, including those using Heikin Ashi candles (as it incorporates real close data to bypass transformations).
The indicator emphasizes visual clarity with color-coded elements: bullish trends in shades of green/lime and bearish in red/maroon. It includes customizable toggles for each component, allowing users to focus on specific features without cluttering the chart.
Key Features
• EMA Ribbon & Glow System:
o Displays a ribbon formed by three EMAs (5, 20, and 50 periods) with gradient fills between them, colored based on trend strength.
o A dynamic "glow" zone around the 50-period EMA, calculated using ATR (Average True Range), acts as a volatility-based support (bullish) or resistance (bearish) band. The glow expands/contracts with market volatility, providing a visual buffer for potential price reactions.
o Real Close Dot: A small circle plotted at the actual closing price of each bar (sourced from standard candles), aiding in precise data verification even on transformed charts like Heikin Ashi.
• Structural Pivots:
o Automatically detects and labels confirmed pivot highs and lows using customizable symbols (e.g., arrows, dots, or curves).
o Draws breakout lines connecting pivots to the bar where structure is broken (Break of Structure - BOS), highlighting bullish (green) or bearish (red) shifts.
o Pivots are trend-aware: In uptrends, it tracks higher highs/lows until a downside break; in downtrends, lower highs/lows until an upside break.
• Real ATR Display:
o A compact table at the bottom-center of the chart showing the current 14-period ATR value (calculated on real data), useful for gauging volatility and setting stop-losses or targets.
How It Works
• EMA Ribbon Logic: The fast EMA (5) is compared to the mid (20), and mid to slow (50), to determine sub-trends. Price relative to the slow EMA sets the overall bullish/bearish bias. Fills create a "ribbon" effect, with colors intensifying in strong trends.
• Glow Zone: Uses a user-defined ATR length and multiplier to create upper/lower bands around the slow EMA. The glow is one-sided: below for bullish (support) and above for bearish (resistance), with semi-transparent shading for easy price overlay.
• Pivot Detection: Tracks the current trend direction (up or down) and reference high/low from the last confirmed pivot. A breakout (close crossing the reference level) confirms a new pivot, labels it, and optionally draws a line to the breakout bar. Bar coloring (yellow) highlights breakout candles.
• Data Handling: All calculations use real close prices via request.security to ensure accuracy on non-standard chart types.
Settings and Customization
The indicator is divided into intuitive input groups for easy configuration:
1. EMA Ribbon & Glow:
o Show EMA Ribbon & Glow: Master toggle to enable/disable the entire ribbon and glow (default: true). Note: Real Close Dot is independent.
o ATR Length (Glow): Lookback for ATR calculation (default: 3; higher = smoother glow).
o ATR Multiplier (Glow Size): Scales the glow width (default: 0.15; higher = wider zone).
o Show Real Close Dot: Toggle for the orange dot at real closes (default: true).
o Real Close Dot Color: Customize the dot's color (default: orange).
2. Structural Pivots:
o Show Pivot Labels: Toggle visibility of high/low symbols (default: true).
o Pivot Symbol Style: Choose from pairs like "︽ ︾" (low/high) or "•" (dots) (default: "•").
o Label Size: Adjust symbol size (Tiny to Huge; default: Normal).
o Pivot High/Low Label Colors: Set colors for labels (default: white).
o Show Breakout Lines: Toggle lines from pivot to breakout (default: true).
o Line Width: Thickness of breakout lines (default: 2).
o Line Style: Solid, Dashed, or Dotted (default: Solid).
o Resistance Break Line (Bullish): Color for upside breaks (default: green).
o Support Break Line (Bearish): Color for downside breaks (default: red).
No additional inputs are required for the ATR table, as it's always displayed on the last bar for quick reference.
Usage Tips
• Trend Identification: Use the EMA ribbon colors to gauge momentum—full green for strong bulls, red for bears. The glow zone can act as a dynamic entry/exit area (e.g., buy near bullish glow support).
• Breakout Trading: Watch for pivot labels and BOS lines as signals for trend reversals. Combine with volume or other indicators for confirmation.
• Volatility Awareness: The displayed ATR(14) helps in position sizing; for example, set stops at 1-2x ATR from entry.
• Chart Compatibility: Works best on candlestick or Heikin Ashi charts. For lower timeframes, reduce ATR length for faster reactivity; increase for higher timeframes.
• Limitations: Pivots are reactive and may lag in ranging markets. Glow is based on historical ATR, so it doesn't predict future volatility.
This indicator is in beta (v1.0) and open to feedback for improvements. Add it to your chart via TradingView's indicator search and experiment with settings to fit your strategy!
MARKET Structure + MTF DashboardThis script automatically detects market structure shifts and visualizes:
Bullish BOS (Break of Structure)
Bearish BOS
Bullish CHoCH (Change of Character)
Bearish CHoCH
On top of that, it shows a multi-timeframe dashboard in the top-right corner of the chart, so you can instantly see the latest structure event on:
1m
6m
36m
216m
1D
regardless of which timeframe you are currently viewing.
Core Logic
The script is built around swing highs / swing lows using ta.pivothigh and ta.pivotlow.
Pivot Definition
A swing high / low is defined by:
lb = left bars
rb = right bars
A pivot high is a bar whose high is higher than the previous lb bars and the next rb bars.
A pivot low is a bar whose low is lower than the previous lb bars and the next rb bars.
Break Conditions
After a pivot is confirmed, the script waits at least N bars (minBarsAfterPivot) before accepting any break of that pivot level as a valid structure event.
You can choose how to define the break:
Close-based (닫기) – use candle close
Wick-based (없음 or 꼬리) – use high/low (full wick)
BOS vs CHoCH Classification
For each timeframe, the script tracks structure breaks and classifies them:
A move breaking above the last swing high → upward break
A move breaking below the last swing low → downward break
Then:
If the current break direction is the same as the previous break
→ it is classified as BOS (trend continuation)
If the current break direction is the opposite of the previous break
→ it is classified as CHoCH (trend reversal / change of character)
Return codes (internally):
1 = Bullish BOS
2 = Bullish CHoCH
-1 = Bearish BOS
-2 = Bearish CHoCH
0 = no event
Chart Annotations
On the active chart timeframe, the script can optionally show:
Structure lines:
Horizontal lines at the price level where BOS / CHoCH occurred
Lines extend to the left until the first candle that previously touched that price zone
Labels:
“Bull BOS”, “Bear BOS”, “Bull CHoCH”, “Bear CHoCH”
Fully color-customizable (line color, label background, text color, transparency)
You can also enable/disable pivot labels (HH, HL, LL, LH) for swing highs and lows, with separate toggles for:
HH / LL
HL / LH
Multi-Timeframe Dashboard
The dashboard in the top-right corner shows, for each timeframe:
1m / 6m / 36m / 216m / 1D
The last structure event (Bull BOS, Bull CHoCH, Bear BOS, Bear CHoCH, or None)
Colored background by event type:
Strong green / red for CHoCH
Softer green / red for BOS
Gray for None
The important part:
Each timeframe’s state is calculated inside that timeframe itself and then pulled via request.security().
That means:
No matter which chart timeframe you are currently on,
the dashboard always shows the same last event for each TF.
Inputs
Pivot lb / Pivot rb
Control how “wide” a swing must be to be accepted as a pivot.
Breakout 기준 (Confirm type)
Close-based or wick-based break logic.
피봇 이후 최소 대기 캔들 수 (Min bars after pivot)
Minimum number of bars that must pass after a pivot forms before a break can count as BOS / CHoCH.
This filters out very early / noisy breaks.
Toggles:
Show pivot balloons (HH/HL/LL/LH)
Show BOS
Show CHoCH
Visual:
Line colors for each event type
Line transparency
Label background transparency
Label text color
Alerts
The script defines alert conditions for:
Bullish BOS
Bearish BOS
Bullish CHoCH
Bearish CHoCH
You can use them to trigger notifications when a new structure event occurs on the active timeframe.
Notes & Usage
This is a market structure helper, not a complete trading system.
BOS / CHoCH should be used together with:
Liquidity zones
Volume / delta
Orderflow or higher-timeframe context
Parameters like lb, rb, and minBarsAfterPivot are intentionally exposed so you can tune:
Sensitivity vs. reliability
Scalping vs. swing-structure
This script is for educational purposes only and does not constitute financial advice.
Always backtest and combine with your own trading plan and risk management.
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.
________________________________________
📊 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.
________________________________________
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.
________________________________________
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)
________________________________________
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)
---
*For questions or support, please comment below. If you find this script valuable, please boost and favorite!* 🚀
Ultimate Multi-Asset Correlation System by able eiei Ultimate Multi-Asset Correlation System - User Guide
Overview
This advanced TradingView indicator combines WaveTrend oscillator analysis with comprehensive multi-asset correlation tracking. It helps traders understand market relationships, identify regime changes, and spot high-probability trading opportunities across different asset classes.
Key Features
1. WaveTrend Oscillator
Main Signal Lines: WT1 (blue) and WT2 (red) plot momentum and its moving average
Overbought/Oversold Zones: Default levels at +60/-60
Cross Signals:
🟢 Bullish: WT1 crosses above WT2 in oversold territory
🔴 Bearish: WT1 crosses below WT2 in overbought territory
Higher Timeframe (HTF) Analysis: Shows WT1 from 4H, Daily, and Weekly timeframes for trend confirmation
2. Multi-Asset Correlation Tracking
Monitors relationships between:
Major Assets: Gold (XAUUSD), Dollar Index (DXY), US 10-Year Yield, S&P 500
Crypto Assets: Bitcoin, Ethereum, Solana, BNB
Cross-Asset Analysis: Correlation between traditional markets and crypto
3. Market Regime Detection
Automatically identifies market conditions:
Risk-On: High correlation + positive sentiment (🟢 Green background)
Risk-Off: High correlation + negative sentiment (🔴 Red background)
Crypto-Risk-On: Strong crypto correlations (🟠 Orange background)
Low-Correlation: Divergent market behavior (⚪ Gray background)
Neutral: Mixed signals (🟡 Yellow background)
How to Use
Basic Setup
Add to Chart: Apply the indicator to any chart (works on all timeframes)
Choose Display Mode (Display Options):
All: Shows everything (recommended for comprehensive analysis)
WaveTrend Only: Focus on momentum signals
Correlation Only: View market relationships
Heatmap Only: Simplified correlation view
Enable Asset Groups:
✅ Major Assets: Traditional markets (stocks, bonds, commodities)
✅ Crypto Assets: Digital currencies
Mix and match based on your trading focus
Reading the Charts
WaveTrend Section (Bottom Panel)
Above 0 = Bullish momentum
Below 0 = Bearish momentum
Above +60 = Overbought (potential reversal)
Below -60 = Oversold (potential bounce)
Lighter lines = Higher timeframe trends
Correlation Histogram (Colored Bars)
Blue bars: Major asset correlations
Orange bars: Crypto correlations
Purple bars: Cross-asset correlations
Bar height: Correlation strength (-50 to +50 scale)
Background Color
Intensity reflects correlation strength
Color shows market regime
Dashboard Elements
🎯 Market Regime Analysis (Top Left)
Current Regime: Overall market condition
Average Correlation: Strength of relationships (0-1 scale)
Risk Sentiment: -100% (risk-off) to +100% (risk-on)
HTF Alignment: Multi-timeframe trend agreement
Signal Quality: Confidence level for current signals
📊 Correlation Matrix (Top Right)
Shows correlation values between asset pairs:
1.00: Perfect positive correlation
0.75+: Strong correlation (🟢 Green)
0.50+: Medium correlation (🟡 Yellow)
0.25+: Weak correlation (🟠 Orange)
Below 0.25: Negative/no correlation (🔴 Red)
🔥 Correlation Heatmap (Bottom Right)
Visual matrix showing:
Gold vs. DXY, BTC, ETH
DXY vs. BTC, ETH
BTC vs. ETH
Color-coded strength
📈 Performance Tracker (Bottom Left)
Tracks individual asset momentum:
WT1 Values: Current momentum reading
Status: OB (overbought) / OS (oversold) / Normal
Trading Strategies
1. High-Probability Trend Following
✅ Entry Conditions:
WaveTrend bullish/bearish cross
HTF Alignment matches signal direction
Signal Quality > 70%
Correlation supports direction
2. Regime Change Trading
🎯 Watch for regime shifts:
Risk-Off → Risk-On = Consider long positions
High correlation → Low correlation = Reduce position size
Crypto-Risk-On = Focus on crypto longs
3. Divergence Trading
🔍 Look for:
Strong correlation breakdown = Potential volatility
Cross-asset correlation surge = Follow the leader
Volume-price correlation extremes = Trend confirmation
4. Overbought/Oversold Reversals
⚡ Trade reversals when:
WT crosses in extreme zones (-60/+60)
HTF alignment shows opposite trend weakening
Correlation confirms mean reversion setup
Customization Tips
Fine-Tuning Parameters
WaveTrend Core:
Channel Length (10): Lower = more sensitive, Higher = smoother
Average Length (21): Adjust for your timeframe
Correlation Settings:
Length (50): Longer = more stable, Shorter = more responsive
Smoothing (5): Reduce noise in correlation readings
Market Regime:
Risk-On Threshold (0.6): Lower = earlier regime signals
High Correlation Threshold (0.75): Adjust sensitivity
Custom Asset Selection
Replace default symbols with your preferred markets:
Major Assets: Any forex, indices, bonds
Crypto: Any digital currencies
Must use correct exchange prefix (e.g., BINANCE:BTCUSDT)
Alert System
Enable "Advanced Alerts" to receive notifications for:
✅ Market regime changes
✅ Correlation breakdowns/surges
✅ Strong signals with high correlation
✅ Extreme volume-price correlation
✅ Complete HTF alignment
Correlation Interpretation Guide
ValueMeaningTrading Implication+0.75 to +1.0Strong positiveAssets move together+0.5 to +0.75Moderate positiveGenerally aligned+0.25 to +0.5Weak positiveLoose relationship-0.25 to +0.25No correlationIndependent movements-0.5 to -0.25Weak negativeSlight inverse relationship-0.75 to -0.5Moderate negativeTend to move opposite-1.0 to -0.75Strong negativeStrongly inversely correlated
Best Practices
Use Multiple Timeframes: Check HTF alignment before trading
Confirm with Correlation: Strong signals work best with supportive correlations
Watch Regime Changes: Adjust strategy based on market conditions
Volume Matters: Enable volume-price correlation for confirmation
Quality Over Quantity: Trade only high-quality setups (>70% signal quality)
Common Patterns to Watch
🔵 Risk-On Environment:
Gold-BTC positive correlation
DXY negative correlation with risk assets
High crypto correlations
🔴 Risk-Off Environment:
Flight to safety (Gold up, stocks down)
DXY strength
Correlation breakdowns
🟡 Transition Periods:
Low correlation across assets
Mixed HTF signals
Use caution, reduce position sizes
Technical Notes
Calculation Period: Uses HLC3 (average of high, low, close)
Correlation Window: Rolling correlation over specified length
HTF Data: Accurately calculated using security() function
Performance: Optimized for real-time calculation on all timeframes
Support
For optimal performance:
Use on 15-minute to daily timeframes
Enable only needed asset groups
Adjust correlation length based on trading style
Combine with your existing strategy for confirmation
Enjoy comprehensive multi-asset analysis! 🚀
Larry Williams COT Analysis Enhanced [tradeviZion]Larry Williams COT Analysis Enhanced - Complete Description
📖 Introduction
Welcome to the Larry Williams COT Analysis Enhanced indicator. This comprehensive description explains every setting, feature, and capability of this advanced Commitments of Traders (COT) analysis tool.
This indicator implements Larry Williams' professional COT analysis methodology with enhanced features including statistical validation, combination analysis, and adaptive signal generation.
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🎯 Quick Start
Add the indicator to your chart
The script will automatically detect your symbol's CFTC code and asset type
Review the main COT analysis table (displayed by default)
Customize settings based on your trading style
Review the Trading Edge & Signals section for signal information
---
⚙️ Settings Groups Overview
The indicator is organized into 9 logical groups of settings:
1. Core COT Settings - Data source and report configuration
2. Analysis Parameters - Calculation methods and lookback periods
3. Signal Generation - Buy/sell signals and trend weighting
4. Plot Display Settings - Visual customization of chart lines
5. Smoothing Settings - Data smoothing options
6. COT Proximity Index Settings - Price-based proxy indicator configuration
7. Common Table Settings - Shared table appearance
8. Main Table Display Settings - Main analysis table customization
9. Historical Comparison Settings - Historical data table configuration
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📋 Group 1: Core COT Settings
COT Report Type
Options: Legacy | Disaggregated | Financial
What it is: Selects the type of COT report data to analyze.
Legacy - Traditional COT report format. Recommended for most users. Uses "Commercial Positions" and "Noncommercial Positions" metrics. Shows Commercial, Non-Commercial, and Small Speculator positions in the classic format.
Commercials: "Commercial Positions"
Speculators: "Noncommercial Positions"
Small Specs: "Nonreportable Positions"
Disaggregated - Separates managed money from other speculators. Uses different metrics than Legacy format.
Commercials: "Producer Merchant Positions"
Speculators: "Managed Money Positions"
Small Specs: "Nonreportable Positions"
Important: When using Disaggregated report type, the table will still show "Non-Comm" as the label, but the data displayed is actually " Managed Money Positions " (hedge funds and CTAs). The underlying data changes based on your report type selection, even though the table label remains "Non-Comm" for consistency.
Where you'll see this data:
📊 Current Positions section - The "Non-Comm" row shows Managed Money long, short, and net positions
📊 Open Interest Analysis section - "Non-Comm" net changes reflect Managed Money position changes
📈 Analysis section - "Non-Comm" percentile and LW Index values are calculated from Managed Money positions
Chart plots - The blue "Non-Commercial" line shows Managed Money net positions
Useful when you want to analyze hedge funds (Managed Money) separately from other large speculators. The "Commercial" row will show " Producer Merchant Positions " instead of general "Commercial Positions".
Financial - Designed for financial instruments (currencies, bonds, stock indices). Uses financial-specific metrics.
Commercials: "Dealer Positions"
Speculators: "Leveraged Funds Positions"
Small Specs: "Nonreportable Positions"
Important: When using Financial report type, the table will still show "Commercial" and "Non-Comm" as labels, but the data displayed is actually " Dealer Positions " (commercials) and " Leveraged Funds Positions " (speculators). The underlying data changes based on your report type selection.
Where you'll see this data:
📊 Current Positions section - "Commercial" row shows Dealer long/short/net, "Non-Comm" row shows Leveraged Funds positions
📊 Open Interest Analysis section - Net changes reflect Dealer and Leveraged Funds position changes
📈 Analysis section - Percentile and LW Index values are calculated from Dealer and Leveraged Funds positions
Chart plots - Lines show Dealer and Leveraged Funds net positions
Use this for currency futures, bond futures, and stock index futures.
Trading Use: Most traders use Legacy as it provides the most comprehensive view and works with all asset types. Switch to Disaggregated if you want to analyze managed money positions separately. Use Financial specifically for financial instruments (currencies, bonds, stock indices).
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Include Options Data
Default: Off (false)
What it is: Toggles whether to include options positions in addition to futures positions.
Trading Use: Larry Williams observed no significant difference in COT analysis when including options data. Keep this disabled unless you specifically need options data. Most traders leave it off for cleaner analysis.
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Auto-detect CFTC Code
Default: On (true)
What it is: Automatically finds the correct CFTC code for your symbol.
Trading Use: Keep this enabled unless you need a specific CFTC code. The script automatically detects codes for:
- Currency futures: CME:6E1! , CME:6B1! , CME:6J1!
- Stock index futures: CME_MINI:ES1! , CBOT_MINI:YM1! , CME_MINI:NQ1!
- Commodities: NYMEX:CL1! , COMEX:GC1! , CBOT:ZC1!
- And many more
Only disable if you're analyzing a symbol that requires a specific CFTC code not in the auto-detection database.
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Manual CFTC Code
Default: Empty
What it is: Enter a specific CFTC code manually (e.g. for E-mini S&P 500). "13874+"
Trading Use: Only used when Auto-detect CFTC Code is disabled. Most users never need this setting.
---
📊 Group 2: Analysis Parameters
Display Mode
Options: COT Report | COT Index | COT Proximity Index
What it is: Controls what data is displayed on the chart and in the table.
COT Report - Shows raw position data (Long, Short, Net positions) plus analysis. Best for detailed analysis. Displays Commercial, Non-Commercial, Small Speculator, and Open Interest lines.
COT Index - Shows index values based on your selected Analysis Method (Percentile or LW Index). Best for quick sentiment analysis. Displays index lines for Commercial, Non-Commercial, Small Speculator, and Open Interest. Percentile can exceed 0-100% for extremes, LW Index stays 0-100%.
Percentile can exceed 0-100% for extremes
LW Index stays 0-100%
COT Proximity Index - Shows a price-based proxy indicator. Useful when COT data is delayed or unavailable. Calculates sentiment based on price action patterns.
Trading Use:
- Use COT Report for comprehensive analysis
- Use COT Index when you want to focus on extreme sentiment levels
- Use COT Proximity Index as a backup when COT data is delayed or unavailable.
---
Analysis Method
Options: Percentile | LW Index
What it is: Selects the calculation method for position rankings.
Percentile - Professional approach. Excludes current bar from range calculation. Can show extremes (>100% or <0%) when today's value breaks historical range. More sensitive to recent extremes.
LW Index - Original Larry Williams method. Includes current bar in range, always 0-100%. Traditional approach.
Trading Use:
Percentile - Better for catching new extremes and recent market shifts
LW Index - Better for traditional Larry Williams analysis
Most traders prefer Percentile for its ability to show when positions break historical ranges.
---
Lookback Mode
Options: Auto | Manual
What it is: Controls how the historical lookback period is determined.
Auto - Automatically sets lookback period based on detected asset type
Manual - Choose your own lookback period
Trading Use: Use Auto unless you have a specific reason to customize. The script automatically sets optimal periods:
Currencies: 26 weeks
Metals: 13 weeks
Grains: 26 weeks
Stocks/Indices: 13 weeks
Bonds: 52 weeks
Energies: 13 weeks
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Manual Lookback Period
Options: 1 Month | 3 Months | 6 Months | 1 Year | 3 Years | Asset-specific presets | Manual
What it is: How far back to look for historical comparison. Only used when Lookback Mode is set to Manual .
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Manual Lookback Weeks
Default: 18 weeks | Range: 1-500
What it is: Exact number of weeks to look back. Only used when Manual Lookback Period is set to Manual .
Trading Use: Set a custom period if you want precise control. 18 weeks = approximately one quarter (3 months).
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🎯 Group 3: Signal Generation
Show Signal Arrows
Default: Off (false)
What it is: Displays buy/sell arrows on the chart when extreme positions are detected.
Trading Use: Enable to get visual alerts for signals. Signals use strict multi-factor conditions requiring:
- Commercial extreme positioning
- Speculator positioning alignment
- Open Interest confirmation
- Trend consistency
- And more...
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Show Background Colors
Default: Off (false)
What it is: Colors the chart background during extreme market conditions.
Trading Use: Enable for visual market state awareness:
- Strong signals = Darker background colors
- Moderate signals = Lighter background colors
- Green background = Bullish extreme
- Red background = Bearish extreme
Useful for quick visual assessment of market conditions.
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Use Price Trend Weighting
Default: On (true)
What it is: Weights signals based on price trend alignment.
How it works:
Uptrend + Commercials long = Stronger bullish signal
Downtrend + Commercials short = Stronger bearish signal
Counter-trend signals = Harder to trigger (more conservative)
Trading Use: Keep enabled for more reliable signals. Commercials aligned with price trend are historically more accurate.
This feature makes signals easier to trigger when commercials align with the trend and harder when they're counter-trend.
---
Trend MA Period
Default: 40 | Range: 1-200
What it is: Moving average period for price trend detection.
How it works:
Price above MA with the MA rising = Uptrend
Price below MA with the MA declining = Downtrend
---
📈 Group 4: Plot Display Settings
Commercial Line Settings
Default Color: Red | Default Width: 2
What it is: Controls the Commercial traders net position line appearance.
Trading Use: Commercials are considered "smart money." Watch for:
Extreme long positions (high index ≥74%) = Heavy buyers = BULLISH signal
Extreme short positions (low index ≤26%) = Heavy sellers = BEARISH signal
Red is traditional for commercials. When Commercials are heavy buyers (high index), it's a bullish signal. When they're heavy sellers (low index), it's a bearish signal.
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Non-Commercial Line Settings
Default Color: Blue | Default Width: 2
What it is: Controls the Non-Commercial (Large Speculators) net position line appearance.
Trading Use: Large speculators are often trend-followers. Watch for:
Extreme long = Potential top (contrarian sell signal)
Extreme short = Potential bottom (contrarian buy signal)
They're often wrong at extremes - use as contrarian indicator.
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Small Speculator Line Settings
Default Color: Green | Default Width: 2
What it is: Controls the Small Speculators net position line appearance.
Trading Use: Small specs are typically wrong at extremes:
Extreme long = Potential top (sell signal)
Extreme short = Potential bottom (buy signal)
Exception: In Meats markets, small specs are accurate (like commercials).
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Small Speculator Multiplier
Default: 5.0x | Range: 0.1-20.0
What it is: Multiplies Small Speculator PLOTTED values for visual comparison.
Important: This only affects the visual plot line, NOT calculations or table values. Raw values used in all calculations remain unchanged.
Trading Use: Small spec positions are often much smaller than commercials. Use multiplier (default 5.0x) to scale the line for easier visual comparison.
---
Open Interest Line Settings
Default Color: Black | Default Width: 1
What it is: Controls the Open Interest line appearance.
Trading Use: Open Interest shows market participation:
Rising OI = New money entering (confirms trend)
Falling OI = Money leaving (potential reversal)
Watch WHO is driving OI changes - This is critical
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Scale Open Interest
Default: On (true)
What it is: Scales Open Interest values to fit chart range.
Important: Only affects plotted lines, not table values. Scaling changes based on lookback period:
- Shorter lookback = More compressed range
- Longer lookback = Wider range
Trading Use: Keep enabled for better visual comparison. Disable if you want absolute OI values.
---
Show Reference Lines
Default: Off (false)
What it is: Toggles the display of horizontal reference lines at 0%, 50%, and 100% levels on the chart.
What it shows:
Zero Line (0%) - Dotted gray line at 0% level
Midline (50%) - Solid gray line at 50% level
100 Line (100%) - Dotted gray line at 100% level
Trading Use: Enable when you want visual reference points for:
0% = Extreme bearish positioning
50% = Neutral/middle range
100% = Extreme bullish positioning
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🔄 Group 5: Smoothing Settings
Smoothing Method
Options: None | SMA | EMA | WMA | RMA
What it is: Selects the moving average type for smoothing data.
None - Use raw data (no smoothing)
SMA - Simple Moving Average (equal weight to all periods)
EMA - Exponential Moving Average (more weight to recent data)
WMA - Weighted Moving Average (linear weighting)
RMA - Relative Moving Average (Wilder's smoothing)
Trading Use:
None - Best for catching extremes quickly
SMA - Most common, balanced smoothing
EMA - More responsive to recent changes
WMA/RMA - Advanced smoothing methods
Smoothing reduces noise but may delay signal detection. Use None for most responsive signals.
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Smoothing Period
Default: 4 | Range: 2-20
What it is: Number of periods for the moving average smoothing.
Trading Use:
Shorter periods (2-5) = Less smoothing, more responsive
Longer periods (10-20) = More smoothing, less noise
Default 4 = Good balance
Only used when Smoothing Method is not None.
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Smooth COT Report Plots
Default: Off (false)
What it is: Applies smoothing to COT Report plotted lines (Commercial, Non-Commercial, Small Speculators, Open Interest).
Trading Use: Enable if you want smoother chart lines. Note: Smoothing affects visual display but calculations use raw data unless Smooth COT Index Plots is also enabled.
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Smooth COT Index Plots
Default: Off (false)
What it is: Applies smoothing to COT Index plotted lines.
Trading Use: Enable if you want smoother index lines. Important : When enabled, smoothed values are used in table displays and signal calculations. This affects the "user-facing" index values shown in the table and used for signals.
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📊 Group 6: COT Proximity Index Settings
Proximity Length Mode
Options: Auto | Manual
What it is: Controls how the proximity index calculation period is determined.
Auto - Calculates length based on ZigZag patterns (dynamic)
Manual - Uses fixed length setting
Trading Use: Use Auto for adaptive calculation. Use Manual if you want consistent period regardless of market conditions.
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Manual Proximity Length
Default: 8 bars | Range: 1+
What it is: Fixed number of bars for COT Proximity Index calculation. Only used when Proximity Length Mode is Manual .
Trading Use: Set based on your timeframe. 8 bars works well for weekly chart.
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Heavy Buyers Level
Default: 74% | Range: 50-100
What it is: COT Index level above which commercials are considered heavy buyers (extreme long positioning).
Trading Use: This threshold is used for:
- Signal generation
- Market state calculation
- Entry level recommendations
Default 74% means commercials are "heavy buyers" when LW Index ≥ 74%.
---
Heavy Sellers Level
Default: 26% | Range: 0-50
What it is: COT Index level below which commercials are considered heavy sellers (extreme short positioning).
Trading Use: This threshold is used for:
- Signal generation
- Market state calculation
- Entry level recommendations
Default 26% means commercials are "heavy sellers" when LW Index ≤ 26%.
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ZigZag Deviation
Default: 1.0% | Range: 1-100.0
What it is: Minimum price change (%) required to create a new ZigZag pivot point.
Trading Use:
Smaller values = More sensitive, more pivots
Larger values = Less sensitive, fewer pivots
Used for Auto proximity length calculation.
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ZigZag Depth
Default: 1 | Range: 1+
What it is: Minimum number of bars between pivot points.
Trading Use: Higher values filter out minor pivots. Default 1 captures all significant pivots.
---
Extend ZigZag to Last Bar
Default: Off (false)
What it is: Draws ZigZag lines to the current bar (may show incomplete patterns).
Trading Use: Enable to see current ZigZag pattern, but be aware it may change as new bars form.
---
Show ZigZag Lines
Default: Off (false)
What it is: Displays ZigZag pivot lines on the chart for visual reference.
Trading Use: Enable to see the ZigZag pattern used for proximity index calculation. Useful for understanding how Auto mode works.
---
🎨 Group 7: Common Table Settings
Color Theme
Options: Dark | Light | Midnight Blue | Ocean Blue | Forest Green | Amber Gold | Slate Gray
What it is: Color scheme for both main and historical comparison tables.
Trading Use: Choose based on your preference:
Dark/Light - Classic themes
Midnight Blue - Professional dark theme
Ocean Blue - Calming blue tones
Forest Green - Natural green theme
Amber Gold - Warm gold tones
Slate Gray - Modern gray theme
Theme applies to both tables simultaneously for consistency.
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📋 Group 8: Main Table Display Settings
Show COT Table
Default: On (true)
What it is: Toggles the main COT analysis table display.
Trading Use: Disable only if you want to use chart plots only. Most traders keep this enabled for comprehensive analysis.
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Table Mode
Options: Full | Compact
What it is: Controls the detail level of the main table.
Full - Complete analysis table with all sections
Compact - Essential info only (mobile-friendly)
Trading Use:
Full - Desktop trading, comprehensive analysis
Compact - Mobile trading, quick reference
See "Table Modes Explained" section below for details.
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Table Position
Options: Top Right | Top Left | Bottom Right | Bottom Left | Middle Right | Middle Left
What it is: Position of the main COT analysis table on the chart.
Trading Use: Choose based on your chart layout and preference. Top Right is default and works well for most traders.
---
Table Text Size
Options: Tiny | Small | Normal | Large
What it is: Size of text in the COT analysis table.
---
Section Visibility Controls
All default: On (true)
What it is: Individual toggles to show/hide specific table sections.
⚙️ Settings - Report Type, CFTC Code, Options setting
📊 Current Positions - Long, Short, Net positions for each group
📈 Analysis - LW Index, Percentile, Market State
🎯 Trading Edge & Signals - Current Signal, Entry Level, Best Setup
💡 Trading Tips - Context-aware trading insights
📈 Trend Analysis - Trend Direction, Strength, Cum Change, ROC, vs MA
🔄 Market Maker Activity - Spreading, Activity Level, Trading Edge
Trading Use: Customize your table to show only what you need:
Quick traders - Show only Trading Edge & Signals
Detailed analysis - Show all sections
Mobile users - Hide less critical sections
Each section can be toggled independently for maximum customization.
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📊 Group 9: Historical Comparison Settings
Show Historical Comparisons
Default: On (true)
What it is: Toggles the historical comparison table display.
Trading Use: This table shows how current positions rank over different time periods (1M, 3M, 6M, 1Y, 3Y, All Time). Very useful for context.
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Historical Table Mode
Options: Full | Compact
What it is: Controls the detail level of the historical comparison table.
Full - Complete historical comparison with all time periods (1M, 3M, 6M, 1Y, 3Y, All Time) and all COT groups
Compact - Essential periods only (1M, 3M, 6M, 1Y, All Time) showing Commercial % only
Trading Use:
- Full - Comprehensive historical analysis
- Compact - Quick reference, mobile-friendly
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Table Position (Historical)
Options: Top Right | Top Left | Bottom Right | Bottom Left
What it is: Position of the historical comparison table on the chart.
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Table Text Size (Historical)
Options: Tiny | Small | Normal | Large
What it is: Size of text in the historical comparison table.
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Trading Days
Options: Weekdays | 24/7
What it is: How to calculate time periods for historical comparisons.
Weekdays - Calculate based on trading days only (5 days/week)
24/7 - Include all calendar days (7 days/week), Use for 24/7 markets like cryptocurrencies
Used for both main COT data and COT Proximity Index historical comparisons.
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📊 Table Modes Explained
Full Mode - Main Table
The Full mode displays all available sections:
⚙️ Settings - Report type, CFTC code, options setting
📊 Current Positions - Long, Short, Net for Commercial, Non-Commercial, Small Speculators
📊 Open Interest Analysis - OI value, change, who's driving changes, concentration
📈 Analysis - Percentile ranks, LW Index values, Market State
🎯 Trading Edge & Signals - Current Signal, Entry Level, What to Watch, Best Setup
💡 Trading Tips - Context-aware insights
📈 Trend Analysis - Trend Direction, Strength, Consistency, Cumulative Change, ROC %, vs MA
🔄 Market Maker Activity - Spreading %, Activity Level, Interpretation, Trading Edge
Best for: Desktop trading, comprehensive analysis, detailed market assessment
---
📋 Understanding Each Table Section
This section explains what each part of the main table means and how to use it for trading decisions.
⚙️ Settings Section
Report Type - Shows which COT report format you're using (Legacy, Disaggregated, or Financial). Verify this matches your asset type.
Options - Indicates if options data is included ("Included") or excluded ("Excluded"). Most traders exclude options for cleaner analysis.
CFTC Code - Unique identifier for your futures contract. Shows "Auto" when automatically detected, or displays the manual code if set.
Trading Use: Always verify your CFTC code is correct. Wrong code = wrong data = wrong signals.
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📊 Current Positions Section
Shows the actual position sizes for each trader group.
What Each Column Means:
Long - Total long contracts held by this group
Short - Total short contracts held by this group
Net - Net position (Long - Short). This is the key number.
How to Interpret:
Commercial Net Position:
- Negative (Net Short) = Commercials expect prices to fall
- Positive (Net Long) = Commercials expect prices to rise
- Commercials are "smart money" - their positioning often precedes major moves
Non-Commercial Net Position:
- Positive (Net Long) = Large speculators bullish
- Negative (Net Short) = Large speculators bearish
- Often trend-followers, can be caught at extremes
Small Spec Net Position:
- Positive (Net Long) = Small traders bullish
- Negative (Net Short) = Small traders bearish
- Often contrarian indicator - wrong at extremes
Trading Edge: Watch for extremes in Commercial net positions. When Commercials are heavy buyers (high index ≥74%), it's a bullish signal. When they're heavy sellers (low index ≤26%), it's a bearish signal.
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📊 Open Interest Analysis Section
Open Interest - Total number of outstanding contracts. Shows market participation level.
Change - Week-over-week change in Open Interest. Rising OI = new money entering, Falling OI = money leaving.
Net Changes - Shows which group is driving Open Interest changes. This is Larry Williams' most important insight.
🎯 Critical Question: Who is Driving OI Changes?
EXTREMELY BULLISH SIGNAL (Very Rare - Pay Close Attention):
- Commercials driving OI increase + Commercials raising positions + Uptrend market
- Meaning: Smart money (commercials) accumulating long positions while market is rising
- Action: Extremely bullish - very rare setup, pay close attention to this signal
- This is the strongest bullish signal possible
BULLISH SIGNAL (Strong Buy):
- Commercials driving OI increase + Commercials net long
- Meaning: Smart money accumulating long positions
- Action: Strong bullish setup
BEARISH SIGNAL (Strong Sell - Market Topping):
- Commercials exiting + OI increasing due to Small Specs + Non-Commercials
- Meaning: Smart money leaving while speculative money entering
- Action: Market top forming - most likely scenario for bearish reversal
- This indicates speculative excess and potential market top
BEARISH SIGNAL (Speculative Excess):
- Small Specs + Non-Commercials driving OI increase + They are net long
- Meaning: Speculative excess, "dumb money" driving market
- Action: Bearish reversal likely
Trading Use:
- Rising OI = New money entering (confirms trend)
- Falling OI = Money leaving (potential reversal)
- Watch WHO is driving OI changes - This is critical
- When Commercials drive OI increases while raising positions in an uptrend = Extremely bullish and very rare - pay attention
- When Commercials exit while OI increases due to Small Specs and Non-Commercials = Market topping signal
Concentration - Shows how much of the market is controlled by the largest traders:
- Top 4 - Four largest traders' share of total OI
- Top 8 - Eight largest traders' share of total OI
Trading Use: High concentration (>30%) means fewer dominant players, potential for volatility. Low concentration means more distributed positions, healthier market.
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📈 Analysis Section
Proximity Index (when in COT Proximity Index mode):
- Value: Current proximity index reading (0-100%)
- Length: Number of bars used in calculation
- Status: Heavy Buyers, Heavy Sellers, or Neutral
Analysis Method - Shows whether you're using Percentile or LW Index calculation.
Small Spec Mode - Shows how Small Speculators are interpreted:
- Contrarian (Traditional) - Small specs are wrong at extremes (default)
- Accurate (Meats) - Small specs are accurate like commercials (for Meats markets)
Market State - Overall market sentiment assessment:
- STRONG BULLISH - Multiple factors aligned bullish, strong buy signal
- MODERATE BULLISH - Several bullish factors, moderate buy signal
- LEANING BULLISH - Slight bullish bias, watch for confirmation
- NEUTRAL - Mixed signals, trade with existing trend
- LEANING BEARISH - Slight bearish bias, watch for confirmation
- MODERATE BEARISH - Several bearish factors, moderate sell signal
- STRONG BEARISH - Multiple factors aligned bearish, strong sell signal
Trading Use: Start your analysis here. Market State gives you the overall picture before diving into details.
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🎯 Trading Edge & Signals Section
Current Signal - Shows which combination is active based on current positioning extremes and its expected accuracy percentage:
- Comm+Spec+OI - All three groups at extremes (highest accuracy)
- Comm+Spec - Commercials and specs at extremes (opposite extremes - Larry Williams' favorite)
- Comm+OI - Commercials and Open Interest at extremes (smart money + participation)
- Commercials - Only Commercials at extreme (smart money indicator)
- Wait - No extremes detected, wait for setup
Entry - Trading signal based on Commercial positioning:
- LONG - Commercials are heavy buyers (≥Heavy Buyers Level), bullish signal
- SHORT - Commercials are heavy sellers (≤Heavy Sellers Level), bearish signal
- Wait - Commercials neutral, no clear signal
Best Setup - Shows the historically highest accuracy combination found in the data:
- Comm+Spec+SmallSpec+OI - All four groups aligned (strongest signal)
- Comm+Spec+OI (All) - Commercials + Speculators + Open Interest aligned
- Comm+Spec+SmallSpec - Commercials + Speculators + Small Specs aligned
- Comm+Spec (Both) - Commercials + Speculators (opposite extremes - Larry Williams' favorite)
- Comm+OI (Both) - Commercials + Open Interest (participation confirms smart money)
- Comm+SmallSpec - Commercials + Small Specs (especially strong in Meats markets)
- Commercials Alone - Commercial positioning only (baseline - smart money indicator)
Trading Use: This is your action center . Focus on Entry signals when Market State confirms. Higher accuracy setups (shown in Best Setup) are more reliable.
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💡 Trading Tips Section
Context-aware insights based on current market conditions.
What You'll See:
Commercial positioning assessment (extreme long/short, favorable/unfavorable)
Speculator positioning (contrarian support or warning)
Open Interest guidance (who's driving changes)
Trend assessment (aligning or conflicting)
Information about entry timing, position sizing, and confirmation needs
Trading Use: Review these tips when analyzing. They provide context-specific information tailored to current conditions.
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📈 Trend Analysis Section
Trend Direction - Overall price trend:
- Bullish - Price trending up
- Bearish - Price trending down
- Mixed - No clear direction
Consistency - How stable the trend is:
- Consistent - Trend is stable and maintaining direction
- Mixed - Trend is unstable, direction changing
- Accelerating - Trend is gaining momentum
Strength - Trend intensity:
- Strong - Powerful trend
- Steady - Moderate trend
- Weak - Weak trend
This Week - Net position change this week (percentage).
Cumulative Change - Total net position change over different periods:
- 4W - 4-week cumulative change
- 13W - 13-week cumulative change (one quarter)
- 26W - 26-week cumulative change (half year)
ROC % - Rate of Change percentage over different periods. Shows momentum.
vs MA - Current net position compared to moving average:
- Positive = Above average (strong positioning)
- Negative = Below average (weak positioning)
Trading Use: Align COT signals with trend direction for higher accuracy. When COT signals align with price trend, signals are more reliable. Counter-trend signals require more confirmation.
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🔄 Market Maker Activity Section
Total Spreading - Percentage of open interest in spread positions (simultaneous long and short in different months).
Percentile - Where current spreading level ranks historically. High percentile = unusual spreading activity.
13W Trend - 13-week trend in spreading activity (+ = increasing, - = decreasing).
Activity Level - Market maker activity intensity:
- High - Very active, expect volatility
- Moderate - Normal activity
- Low - Quiet, less volatility expected
vs 13W Avg - Current activity compared to 13-week average.
Trading Edge - Interpretation of market maker activity:
- High & Rising - Expect volatility, market makers hedging risk
- High & Stable - Active hedging, monitor for changes
- Low & Falling - Reduced activity, potential for directional moves
Trading Use: High market maker activity often precedes volatility. Use this to adjust position sizing and risk management. When spreading is high and rising, expect choppy conditions.
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📋 Understanding Compact Mode Fields
The Compact mode provides essential information for quick trading decisions. Here's what each field means:
State
Shows the overall market sentiment based on combined COT analysis.
Possible Values:
- STRONG BULLISH - Multiple factors aligned bullish, strong buy signal
- MODERATE BULLISH - Several bullish factors, moderate buy signal
- LEANING BULLISH - Slight bullish bias, watch for confirmation
- NEUTRAL - Mixed signals, trade with existing trend
- LEANING BEARISH - Slight bearish bias, watch for confirmation
- MODERATE BEARISH - Several bearish factors, moderate sell signal
- STRONG BEARISH - Multiple factors aligned bearish, strong sell signal
Trading Use: Start your analysis here. Strong signals (STRONG BULLISH/BEARISH) indicate higher confidence setups. Neutral means trade with price trend.
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Entry
Your actionable trading signal based on Commercial positioning.
Possible Values:
- LONG - Commercials are heavy buyers (≥Heavy Buyers Level), bullish signal
- SHORT - Commercials are heavy sellers (≤Heavy Sellers Level), bearish signal
- Wait - Commercials neutral, no clear signal
Trading Use: This is your go/no-go decision point. Only take trades when Entry shows LONG or SHORT. When Entry = Wait, stay on sidelines until clearer signal develops.
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Comm Index
Commercial LW Index percentage showing where Commercial net position ranks historically.
Range: 0% to 100%
- 0-26% = Commercials heavy sellers (bearish positioning)
- 27-73% = Commercials neutral (no extreme)
- 74-100% = Commercials heavy buyers (bullish positioning)
Trading Use: Commercial extremes are most reliable. Values ≥74% (heavy buyers/extreme long) = BULLISH signal. Values ≤26% (heavy sellers/extreme short) = BEARISH signal. When Commercials are heavy buyers, it indicates bullish sentiment. When they're heavy sellers, it indicates bearish sentiment.
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OI Status
Open Interest condition showing market participation level and trend.
Format: Status (Percentile %)
Examples:
- High (100.0%) - OI at extreme high, strong participation
- Moderate (50.0%) - OI at average level
- Low (10.0%) - OI at extreme low, weak participation
Trend Indicators:
- Rising - OI increasing (new money entering)
- Falling - OI decreasing (money leaving)
- Stable - OI unchanged
Trading Use: High OI with rising trend = strong market participation, confirms directional moves. Falling OI = watch for potential reversals. Low OI = reduced participation, potential for volatility.
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Best Setup
Shows which combination of factors has the highest historical accuracy.
Format: Combination Name (Accuracy %)
Examples:
- Commercials Alone (75.3%) - Commercial positioning only
- Commercials + Speculators (68.2%) - Commercials and specs aligned
- Commercials + Open Interest (72.1%) - Commercials with OI confirmation
- Commercials + Speculators + OI (82.1%) - All factors aligned (strongest)
Trading Use: Higher accuracy values indicate signals with higher historical accuracy. When Best Setup shows "Commercials + Speculators + OI" with high accuracy, it indicates a combination with strong historical performance.
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Trend
13-week cumulative trend direction based on net position changes.
Possible Values:
- Bullish - Net positions trending bullish over 13 weeks
- Bearish - Net positions trending bearish over 13 weeks
- Mixed - No clear directional trend
Trading Use: Align Entry signals with Trend for higher accuracy. When Entry = LONG and Trend = Bullish, signal is stronger. When Entry = LONG but Trend = Bearish, wait for price confirmation before entering. Counter-trend signals require more confirmation.
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Full Mode - Historical Table
The Full historical mode shows:
All time periods: 1 Month, 3 Months, 6 Months, 1 Year, 3 Years, All Time
All COT groups: Commercial, Non-Commercial, Small Speculators, Open Interest
Complete header with asset type and lookback information
Best for: Comprehensive historical analysis, understanding long-term positioning
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Compact Mode - Historical Table
The Compact historical mode shows:
Essential periods only: 1M, 3M, 6M, 1Y, All Time
Commercial % only (most important indicator)
Simplified header
Best for: Quick reference, mobile-friendly, focused analysis
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🎯 How to Use Each Feature for Trading
Using Display Modes
COT Report Mode - Use for:
Understanding raw position sizes
Analyzing net position changes
Comparing absolute positions across groups
Detailed market structure analysis
COT Index Mode - Use for:
Quick sentiment assessment
Identifying extremes (Percentile can show >100% or <0%, LW Index shows 0-100%)
Comparing relative positioning
Signal generation
COT Proximity Index Mode - Use for:
When COT data is delayed
Real-time sentiment estimation
Price-action based analysis
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Using Analysis Methods
Percentile Method - Use when:
You want to catch new extremes (>100% or <0%)
You need responsive signals
You're analyzing recent market regime changes
You want to use the professional approach (excludes current bar from range)
LW Index Method - Use when:
You want traditional Larry Williams analysis
You prefer stable, conservative signals
You're doing long-term analysis
You want always 0-100% range
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Using Signal Generation
Enable Signal Arrows when:
You want visual alerts for high-quality setups
You're scanning multiple charts
You want to catch extreme positioning
Enable Background Colors when:
You want quick visual market state assessment
You're monitoring multiple timeframes
You want to see market conditions at a glance
Use Price Trend Weighting to:
Increase signal reliability
Align COT signals with price action
Filter counter-trend signals
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Using Smoothing
No Smoothing - Best for:
Catching extremes quickly
Responsive signal generation
Active trading
With Smoothing - Best for:
Reducing noise
Trend identification
Swing trading
Remember: Smoothing affects visual display. Enable "Smooth COT Index Plots" if you want smoothed values in calculations.
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Using Heavy Buyers/Sellers Levels
Default 74%/26% - Good starting point
Tighter levels (80%/20%) - More conservative, fewer signals
Wider levels (70%/30%) - More signals, less extreme
Trading Use: Adjust based on your risk tolerance and signal frequency preference.
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Using Table Sections
Settings - Verify your configuration
Current Positions - Understand current market structure
Analysis - Identify extremes and market state
Trading Edge & Signals - Most important - Entry signals based on Commercial positioning
Trading Tips - Context-aware insights
Trend Analysis - Understand momentum and direction
Market Maker Activity - Assess market maker positioning
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💡 Key Trading Concepts
Market State Interpretation
STRONG BULLISH - Multiple factors aligned bullish. Strong buy signal.
MODERATE BULLISH - Several bullish factors. Moderate buy signal.
LEANING BULLISH - Slight bullish bias. Watch for confirmation.
NEUTRAL - Mixed signals. Trade with existing trend.
LEANING BEARISH - Slight bearish bias. Watch for confirmation.
MODERATE BEARISH - Several bearish factors. Moderate sell signal.
STRONG BEARISH - Multiple factors aligned bearish. Strong sell signal.
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Entry Level Signals
LONG - Commercials are heavy buyers (≥Heavy Buyers Level). Bullish signal.
SHORT - Commercials are heavy sellers (≤Heavy Sellers Level). Bearish signal.
Wait - Commercials neutral. No clear signal.
When Commercials are heavy buyers (high index), it indicates bullish sentiment. When they're heavy sellers (low index), it indicates bearish sentiment.
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Best Setup Interpretation
The Best Setup shows the historically highest accuracy combination:
Commercials Alone - Commercial positioning is most reliable
Commercials + Speculators - Both groups aligned
Commercials + Open Interest - Commercials + OI confirmation
Commercials + Speculators + OI - All factors aligned (strongest)
Higher accuracy = More reliable signal. Use this to prioritize which signals to follow.
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Open Interest Analysis
Critical Question: Who is driving Open Interest changes?
EXTREMELY BULLISH (Very Rare):
Commercials driving OI increase + Commercials raising positions + Uptrend = EXTREMELY BULLISH
This is very rare - pay close attention when this occurs
STRONG BULLISH:
Commercials driving OI increase + Commercials long = STRONG BULLISH
BEARISH (Market Topping):
Commercials exiting + OI increasing due to Small Specs + Non-Commercials = BEARISH (market topping)
Most likely scenario for bearish reversal - speculative excess
BEARISH (Speculative Excess):
Speculators driving OI increase + Speculators long = BEARISH (speculative excess)
TREND CONFIRMATION:
Rising OI = Confirms trend (new money entering)
Falling OI = Potential reversal (money leaving)
This is one of Larry Williams' most important insights. When Commercials drive OI increases while raising positions in an uptrend, it's extremely bullish and very rare - pay attention. When Commercials exit while Small Specs and Non-Commercials drive OI increases, the market is likely topping.
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🚀 Practical Trading Workflow
Daily Analysis Routine
Check Market State - Overall assessment
Review Entry Level - Actionable signal
Check Best Setup - Signal reliability
Review Trading Tips - Context-aware insights
Analyze Trend Analysis - Momentum confirmation
Check Historical Comparison - Context over time
Verify Open Interest - Who's driving changes
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Signal Confirmation Checklist
Before taking a trade based on COT signals:
✓ Market State shows clear bias (not Neutral)
✓ Entry Level matches Market State
✓ Best Setup shows high accuracy (>60%)
✓ Price trend aligns with signal (if using trend weighting)
✓ Open Interest confirms (rising for trend continuation, falling for reversal)
✓ Historical comparison shows extreme positioning
✓ Price action confirms (wait for price confirmation)
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⚠️ Important Notes
COT data is weekly - Updates every Friday afternoon
Extremes can persist - Don't expect immediate reversals
Combine with price action - COT is one tool among many
Historical context matters - Consider market conditions
Meats markets are special - Small specs are accurate (like commercials)
Signals are rare - High-quality signals don't appear every week
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This description covers all settings and features of the Larry Williams COT Analysis Enhanced indicator. Larry Williams recommends combining COT analysis with other indicators for setup signals: Williams Sentiment Index, Williams Valuation Index, Williams True Seasonal, Pinch and Paunch Signal, along with price action, technical analysis, and fundamental factors.
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📖 Conclusion
The Larry Williams COT Analysis Enhanced indicator provides a sophisticated framework for understanding market sentiment through the lens of different participant groups. By combining mathematical analysis with behavioral insights, it displays COT positioning data, calculates index values, and generates signals based on extreme positioning.
Remember: This is a tool for analysis, not a crystal ball. Consider combining COT analysis with other Larry Williams indicators, price action, technical analysis, and fundamental factors.
Practice with the indicator, study historical signals, and develop your understanding of how different market participants behave. Signals with multiple factors aligned - Commercials at extremes, Open Interest changes driven by the right groups, and price action confirming the COT signals - have shown higher historical accuracy.
This description provides comprehensive documentation for the Larry Williams COT Analysis Enhanced indicator. For the most current data and analysis, always refer to the latest COT reports and market conditions.
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Acknowledgment
This tool builds upon the foundational work of Larry Williams, who developed the Commitments of Traders (COT) analysis methodology and the principles for interpreting COT data. It also incorporates enhancements including statistical validation, combination analysis, adaptive signal generation, and comprehensive historical comparison features.
Note: Always practice proper risk management and thoroughly test the indicator to ensure it aligns with your trading strategy. Past performance is not indicative of future results.
Day-Type Detector — Rejection / FNL / Outside / StopRun (Clean)Day-Type Detector — Rejection / FNL / Outside / Stop-Run (Clean Version)
This indicator identifies four high-impact candlestick day-types commonly used in professional price-action and auction-market trading: Rejection Days, Failed New Low (FNL) Days, Outside Days, and Stop-Run Days. These patterns often precede major directional moves, reversals, and absorption events, making them particularly valuable for swing traders, positional traders, and short-term discretionary traders.
The script is designed to work across all timeframes and is built around volatility-adjusted measurements using Average Daily Range (ADR) for accuracy and consistency.
What This Indicator Detects
1. Rejection Day (Bullish & Bearish)
A Rejection Day is a wide-range bar that rejects a previous extreme.
The indicator identifies rejection based on:
Range > ADR × threshold
Long lower wick (for bullish) or long upper wick (for bearish)
Close located in the strong zone of the day’s range
These conditions highlight areas where aggressive counter-orderflow entered the market.
2. Failed New Low (FNL) / Failed New High
An FNL day traps traders who attempted breakout selling or buying.
The indicator checks for:
A break beyond the previous session’s low or high
Immediate rejection back inside
Midpoint recapture conditions
ADR-normalized range requirements
These days often trigger powerful directional reversals.
3. Outside Day (Bullish & Bearish)
An Outside Day is a statistically significant expansion day that breaks both the previous high and low.
The script validates:
High > previous high and low < previous low
Range > ADR threshold
Close beyond prior session extreme to complete the rejection sequence
Outside Days often represent stop runs, shakeouts, or trend accelerations.
4. Stop-Run Day (Bullish & Bearish)
Stop-Run Days are aggressive volatility expansions and tend to be the largest ranges within short windows.
This detector identifies them using:
Range > ADR × multiplier
Close located near the extreme of the day (top for bullish, bottom for bearish)
Strong body relative to total range
Break above/below previous session extreme
These patterns indicate capitulation or forced liquidation and are often followed by continuation or sharp counter-rotation.
Key Features
✔ Historical Pattern Marking
All qualifying bars are marked on the chart using plotshape() in global scope, ensuring full historical visibility.
✔ Event Logging & Table Display
A table (top-right of the chart) displays the most recent pattern detections, including:
Timestamp
Pattern type
Bar index
This allows users to monitor and study past pattern occurrences without scanning the chart manually.
✔ ADR-Adjusted Detection
Volatility uncertainty is removed by anchoring all thresholds to ADR.
This ensures consistency across:
Different symbols
Different timeframes
Different market regimes
✔ Alerts Included
Alerts are preconfigured for:
Rejection Day Bull / Bear
FNL Bull / Bear
Outside Day Bull / Bear
Stop-Run Bull / Bear
This allows the user to receive real-time notifications when major day-type structures develop.
How to Use
Add the indicator to any timeframe chart.
Enable or disable:
Historical markers
History table
ADR diagnostics
Watch for shape markers or use alerts for real-time signals.
Use the history table to review recent occurrences.
Combine these day-types with:
Market structure levels
High/low volume nodes (LVNs)
Support/resistance zones
Trend context
These day-types are most effective when they occur near meaningful structural levels because they show where strong order-flow entered the market.
Best Practices
Use higher timeframes (1H–1D) for swing entries.
Confirm signals with market structure or volume profile.
Treat these day-types as context, not standalone signals.
Observe follow-through behavior in the next 1–3 bars after detection.
Credits
This script is based on concepts commonly seen in auction-market theory and professional price-action frameworks, such as Rejection Days, Failed New Lows, Outside Days, and Stop-Run behaviors.
All calculations and logic have been rebuilt from scratch to ensure clean, reliable, and optimized Pine Script v6 execution.
Luxy Super-Duper SuperTrend Predictor Engine and Buy/Sell signalA professional trend-following grading system that analyzes historical trend
patterns to provide statistical duration estimates using advanced similarity
matching and k-nearest neighbors analysis. Combines adaptive Supertrend with
intelligent duration statistics, multi-timeframe confluence, volume confirmation,
and quality scoring to identify high-probability setups with data-driven
target ranges across all timeframes.
Note: All duration estimates are statistical calculations based on historical data, not guarantees of future performance.
WHAT MAKES THIS DIFFERENT
Unlike traditional SuperTrend indicators that only tell you trend direction, this system answers the critical question: "What is the typical duration for trends like this?"
The Statistical Analysis Engine:
• Analyzes your chart's last 15+ completed SuperTrend trends (bullish and bearish separately)
• Uses k-nearest neighbors similarity matching to find historically similar setups
• Calculates statistical duration estimates based on current market conditions
• Learns from estimation errors and adapts over time (Advanced mode)
• Displays visual duration analysis box showing median, average, and range estimates
• Tracks Statistical accuracy with backtest statistics
Complete Trading System:
• Statistical trend duration analysis with three intelligence levels
• Adaptive Supertrend with dynamic ATR-based bands
• Multi-timeframe confluence analysis (6 timeframes: 5M to 1W)
• Volume confirmation with spike detection and momentum tracking
• Quality scoring system (0-70 points) rating each setup
• One-click preset optimization for all trading styles
• Anti-repaint guarantee on all signals and duration estimates
METHODOLOGY CREDITS
This indicator's approach is inspired by proven trading methodologies from respected market educators:
• Mark Minervini - Volatility Contraction Pattern (VCP) and pullback entry techniques
• William O'Neil - Volume confirmation principles and institutional buying patterns (CANSLIM methodology)
• Dan Zanger - Volatility expansion entries and momentum breakout strategies
Important: These are educational references only. This indicator does not guarantee any specific trading results. Always conduct your own analysis and risk management.
KEY FEATURES
1. TREND DURATION ANALYSIS SYSTEM - The Core Innovation
The statistical analysis engine is what sets this indicator apart from standard SuperTrend systems. It doesn't just identify trend changes - it provides statistical analysis of potential duration.
How It Works:
Step 1: Historical Tracking
• Automatically records every completed SuperTrend trend (duration in bars)
• Maintains separate databases for bullish trends and bearish trends
• Stores up to 15 most recent trends of each type
• Captures market conditions at each trend flip: volume ratio, ATR ratio, quality score, price distance from SuperTrend, proximity to support/resistance
Step 2: Similarity Matching (k-Nearest Neighbors)
• When new trend begins, system compares current conditions to ALL historical flips
• Calculates similarity score based on:
- Volume similarity (30% weight) - Is volume behaving similarly?
- Volatility similarity (30% weight) - Is ATR/volatility similar?
- Quality similarity (20% weight) - Is setup strength comparable?
- Distance similarity (10% weight) - Is price distance from ST similar?
- Support/Resistance proximity (10% weight) - Similar structural context?
• Selects the 15 MOST SIMILAR historical trends (not just all trends)
• This is like asking: "When conditions looked like this before, how long did trends last?"
Step 3: Statistical Analysis
• Calculates median duration (most common outcome)
• Calculates average duration (mean of similar trends)
• Determines realistic range (min to max of similar trends)
• Applies exponential weighting (recent trends weighted more heavily)
• Outputs confidence-weighted statistical estimate
Step 4: Advanced Intelligence (Advanced Mode Only)
The Advanced mode applies five sophisticated multipliers to refine estimates:
A) Market Structure Multiplier (±30%):
• Detects nearby support/resistance levels using pivot detection
• If flip occurs NEAR a key level: Estimate adjusted -30% (expect bounce/rejection)
• If flip occurs in open space: Estimate adjusted +30% (clear path for continuation)
• Uses configurable lookback period and ATR-based proximity threshold
B) Asset Type Multiplier (±40%):
• Adjusts duration estimates based on asset volatility characteristics
• Small Cap / Biotech: +40% (explosive, extended moves)
• Tech Growth: +20% (momentum-driven, longer trends)
• Blue Chip / Large Cap: 0% (baseline, steady trends)
• Dividend / Value: -20% (slower, grinding trends)
• Cyclical: Variable based on macro regime
• Crypto / High Volatility: +30% (parabolic potential)
C) Flip Strength Multiplier (±20%):
• Analyzes the QUALITY of the trend flip itself
• Strong flip (high volume + expanding ATR + quality score 60+): +20%
• Weak flip (low volume + contracting ATR + quality score under 40): -20%
• Logic: Historical data shows that powerful flips tend to be followed by longer trends
D) Error Learning Multiplier (±15%):
• Tracks Statistical accuracy over last 10 completed trends
• Calculates error ratio: (estimated duration / Actual Duration)
• If system consistently over-estimates: Apply -15% correction
• If system consistently under-estimates: Apply +15% correction
• Learns and adapts to current market regime
E) Regime Detection Multiplier (±20%):
• Analyzes last 3 trends of SAME TYPE (bull-to-bull or bear-to-bear)
• Compares recent trend durations to historical average
• If recent trends 20%+ longer than average: +20% adjustment (trending regime detected)
• If recent trends 20%+ shorter than average: -20% adjustment (choppy regime detected)
• Detects whether market is in trending or mean-reversion mode
Three analysis modes:
SIMPLE MODE - Basic Statistics
• Uses raw median of similar trends only
• No multipliers, no adjustments
• Best for: Beginners, clean trending markets
• Fastest calculations, minimal complexity
STANDARD MODE - Full Statistical Analysis
• Similarity matching with k-nearest neighbors
• Exponential weighting of recent trends
• Median, average, and range calculations
• Best for: Most traders, general market conditions
• Balance of accuracy and simplicity
ADVANCED MODE - Statistics + Intelligence
• Everything in Standard mode PLUS
• All 5 advanced multipliers (structure, asset type, flip strength, learning, regime)
• Highest Statistical accuracy in testing
• Best for: Experienced traders, volatile/complex markets
• Maximum intelligence, most adaptive
Visual Duration Analysis Box:
When a new trend begins (SuperTrend flip), a box appears on your chart showing:
• Analysis Mode (Simple / Standard / Advanced)
• Number of historical trends analyzed
• Median expected duration (most likely outcome)
• Average expected duration (mean of similar trends)
• Range (minimum to maximum from similar trends)
• Advanced multipliers breakdown (Advanced mode only)
• Backtest accuracy statistics (if available)
The box extends from the flip bar to the estimated endpoint based on historical data, giving you a visual target for trend duration. Box updates in real-time as trend progresses.
Backtest & Accuracy Tracking:
• System backtests its own duration estimates using historical data
• Shows accuracy metrics: how well duration estimates matched actual durations
• Tracks last 10 completed duration estimates separately
• Displays statistics in dashboard and duration analysis boxes
• Helps you understand statistical reliability on your specific symbol/timeframe
Anti-Repaint Guarantee:
• duration analysis boxes only appear AFTER bar close (barstate.isconfirmed)
• Historical duration estimates never disappear or change
• What you see in history is exactly what you would have seen real-time
• No future data leakage, no lookahead bias
2. INTELLIGENT PRESET CONFIGURATIONS - One-Click Optimization
Unlike indicators that require tedious parameter tweaking, this system includes professionally optimized presets for every trading style. Select your approach from the dropdown and ALL parameters auto-configure.
"AUTO (DETECT FROM TF)" - RECOMMENDED
The smartest option: automatically selects optimal settings based on your chart timeframe.
• 1m-5m charts → Scalping preset (ATR: 7, Mult: 2.0)
• 15m-1h charts → Day Trading preset (ATR: 10, Mult: 2.5)
• 2h-4h-D charts → Swing Trading preset (ATR: 14, Mult: 3.0)
• W-M charts → Position Trading preset (ATR: 21, Mult: 4.0)
Benefits:
• Zero configuration - works immediately
• Always matched to your timeframe
• Switch timeframe = automatic adjustment
• Perfect for traders who use multiple timeframes
"SCALPING (1-5M)" - Ultra-Fast Signals
Optimized for: 1-5 minute charts, high-frequency trading, quick profits
Target holding period: Minutes to 1-2 hours maximum
Best markets: High-volume stocks, major crypto pairs, active futures
Parameter Configuration:
• Supertrend: ATR 7, Multiplier 2.0 (very sensitive)
• Volume: MA 10, High 1.8x, Spike 3.0x (catches quick surges)
• Volume Momentum: AUTO-DISABLED (too restrictive for fast scalping)
• Quality minimum: 40 points (accepts more setups)
• Duration Analysis: Uses last 15 trends with heavy recent weighting
Trading Logic:
Speed over precision. Short ATR period and low multiplier create highly responsive SuperTrend. Volume momentum filter disabled to avoid missing fast moves. Quality threshold relaxed to catch more opportunities in rapid market conditions.
Signals per session: 5-15 typically
Hold time: Minutes to couple hours
Best for: Active traders with fast execution
"DAY TRADING (15M-1H)" - Balanced Approach
Optimized for: 15-minute to 1-hour charts, intraday moves, session-based trading
Target holding period: 30 minutes to 8 hours (within trading day)
Best markets: Large-cap stocks, major indices, established crypto
Parameter Configuration:
• Supertrend: ATR 10, Multiplier 2.5 (balanced)
• Volume: MA 20, High 1.5x, Spike 2.5x (standard detection)
• Volume Momentum: 5/20 periods (confirms intraday strength)
• Quality minimum: 50 points (good setups preferred)
• Duration Analysis: Balanced weighting of recent vs historical
Trading Logic:
The most balanced configuration. ATR 10 with multiplier 2.5 provides steady trend following that avoids noise while catching meaningful moves. Volume momentum confirms institutional participation without being overly restrictive.
Signals per session: 2-5 typically
Hold time: 30 minutes to full day
Best for: Part-time and full-time active traders
"SWING TRADING (4H-D)" - Trend Stability
Optimized for: 4-hour to Daily charts, multi-day holds, trend continuation
Target holding period: 2-15 days typically
Best markets: Growth stocks, sector ETFs, trending crypto, commodity futures
Parameter Configuration:
• Supertrend: ATR 14, Multiplier 3.0 (stable)
• Volume: MA 30, High 1.3x, Spike 2.2x (accumulation focus)
• Volume Momentum: 10/30 periods (trend stability)
• Quality minimum: 60 points (high-quality setups only)
• Duration Analysis: Favors consistent historical patterns
Trading Logic:
Designed for substantial trend moves while filtering short-term noise. Higher ATR period and multiplier create stable SuperTrend that won't flip on minor corrections. Stricter quality requirements ensure only strongest setups generate signals.
Signals per week: 2-5 typically
Hold time: Days to couple weeks
Best for: Part-time traders, swing style
"POSITION TRADING (D-W)" - Long-Term Trends
Optimized for: Daily to Weekly charts, major trend changes, portfolio allocation
Target holding period: Weeks to months
Best markets: Blue-chip stocks, major indices, established cryptocurrencies
Parameter Configuration:
• Supertrend: ATR 21, Multiplier 4.0 (very stable)
• Volume: MA 50, High 1.2x, Spike 2.0x (long-term accumulation)
• Volume Momentum: 20/50 periods (major trend confirmation)
• Quality minimum: 70 points (excellent setups only)
• Duration Analysis: Heavy emphasis on multi-year historical data
Trading Logic:
Conservative approach focusing on major trend changes. Extended ATR period and high multiplier create SuperTrend that only flips on significant reversals. Very strict quality filters ensure signals represent genuine long-term opportunities.
Signals per month: 1-2 typically
Hold time: Weeks to months
Best for: Long-term investors, set-and-forget approach
"CUSTOM" - Advanced Configuration
Purpose: Complete manual control for experienced traders
Use when: You understand the parameters and want specific optimization
Best for: Testing new approaches, unusual market conditions, specific instruments
Full control over:
• All SuperTrend parameters
• Volume thresholds and momentum periods
• Quality scoring weights
• analysis mode and multipliers
• Advanced features tuning
Preset Comparison Quick Reference:
Chart Timeframe: Scalping (1M-5M) | Day Trading (15M-1H) | Swing (4H-D) | Position (D-W)
Signals Frequency: Very High | High | Medium | Low
Hold Duration: Minutes | Hours | Days | Weeks-Months
Quality Threshold: 40 pts | 50 pts | 60 pts | 70 pts
ATR Sensitivity: Highest | Medium | Lower | Lowest
Time Investment: Highest | High | Medium | Lowest
Experience Level: Expert | Advanced | Intermediate | Beginner+
3. QUALITY SCORING SYSTEM (0-70 Points)
Every signal is rated in real-time across three dimensions:
Volume Confirmation (0-30 points):
• Volume Spike (2.5x+ average): 30 points
• High Volume (1.5x+ average): 20 points
• Above Average (1.0x+ average): 10 points
• Below Average: 0 points
Volatility Assessment (0-30 points):
• Expanding ATR (1.2x+ average): 30 points
• Rising ATR (1.0-1.2x average): 15 points
• Contracting/Stable ATR: 0 points
Volume Momentum (0-10 points):
• Strong Momentum (1.2x+ ratio): 10 points
• Rising Momentum (1.0-1.2x ratio): 5 points
• Weak/Neutral Momentum: 0 points
Score Interpretation:
60-70 points - EXCELLENT:
• All factors aligned
• High conviction setup
• Maximum position size (within risk limits)
• Primary trading opportunities
45-59 points - STRONG:
• Multiple confirmations present
• Above-average setup quality
• Standard position size
• Good trading opportunities
30-44 points - GOOD:
• Basic confirmations met
• Acceptable setup quality
• Reduced position size
• Wait for additional confirmation or trade smaller
Below 30 points - WEAK:
• Minimal confirmations
• Low probability setup
• Consider passing
• Only for aggressive traders in strong trends
Only signals meeting your minimum quality threshold (configurable per preset) generate alerts and labels.
4. MULTI-TIMEFRAME CONFLUENCE ANALYSIS
The system can simultaneously analyze trend alignment across 6 timeframes (optional feature):
Timeframes analyzed:
• 5-minute (scalping context)
• 15-minute (intraday momentum)
• 1-hour (day trading bias)
• 4-hour (swing context)
• Daily (primary trend)
• Weekly (macro trend)
Confluence Interpretation:
• 5-6/6 aligned - Very strong multi-timeframe agreement (highest confidence)
• 3-4/6 aligned - Moderate agreement (standard setup)
• 1-2/6 aligned - Weak agreement (caution advised)
Dashboard shows real-time alignment count with color-coding. Higher confluence typically correlates with longer, stronger trends.
5. VOLUME MOMENTUM FILTER - Institutional Money Flow
Unlike traditional volume indicators that just measure size, Volume Momentum tracks the RATE OF CHANGE in volume:
How it works:
• Compares short-term volume average (fast period) to long-term average (slow period)
• Ratio above 1.0 = Volume accelerating (money flowing IN)
• Ratio above 1.2 = Strong acceleration (institutional participation likely)
• Ratio below 0.8 = Volume decelerating (money flowing OUT)
Why it matters:
• Confirms trend with actual money flow, not just price
• Leading indicator (volume often leads price)
• Catches accumulation/distribution before breakouts
• More intuitive than complex mathematical filters
Integration with signals:
• Optional filter - can be enabled/disabled per preset
• When enabled: Only signals with rising volume momentum fire
• AUTO-DISABLED in Scalping mode (too restrictive for fast trading)
• Configurable fast/slow periods per trading style
6. ADAPTIVE SUPERTREND MULTIPLIER
Traditional SuperTrend uses fixed ATR multiplier. This system dynamically adjusts the multiplier (0.8x to 1.2x base) based on:
• Trend Strength: Price correlation over lookback period
• Volume Weight: Current volume relative to average
Benefits:
• Tighter bands in calm markets (less premature exits)
• Wider bands in volatile conditions (avoids whipsaws)
• Better adaptation to biotech, small-cap, and crypto volatility
• Optional - can be disabled for classic constant multiplier
7. VISUAL GRADIENT RIBBON
26-layer exponential gradient fill between price and SuperTrend line provides instant visual trend strength assessment:
Color System:
• Green shades - Bullish trend + volume confirmation (strongest)
• Blue shades - Bullish trend, normal volume
• Orange shades - Bearish trend + volume confirmation
• Red shades - Bearish trend (weakest)
Opacity varies based on:
• Distance from SuperTrend (farther = more opaque)
• Volume intensity (higher volume = stronger color)
The ribbon provides at-a-glance trend strength without cluttering your chart. Can be toggled on/off.
8. INTELLIGENT ALERT SYSTEM
Two-tier alert architecture for flexibility:
Automatic Alerts:
• Fire automatically on BUY and SELL signals
• Include full context: quality score, volume state, volume momentum
• One alert per bar close (alert.freq_once_per_bar_close)
• Message format: "BUY: Supertrend bullish + Quality: 65/70 | Volume: HIGH | Vol Momentum: STRONG (1.35x)"
Customizable Alert Conditions:
• Appear in TradingView's "Create Alert" dialog
• Three options: BUY Signal Only, SELL Signal Only, ANY Signal (BUY or SELL)
• Use TradingView placeholders: {{ticker}}, {{interval}}, {{close}}, {{time}}
• Fully customizable message templates
All alerts use barstate.isconfirmed - Zero repaint guarantee.
9. ANTI-REPAINT ARCHITECTURE
Every component guaranteed non-repainting:
• Entry signals: Only appear after bar close
• duration analysis boxes: Created only on confirmed SuperTrend flips
• Informative labels: Wait for bar confirmation
• Alerts: Fire once per closed bar
• Multi-timeframe data: Uses lookahead=barmerge.lookahead_off
What you see in history is exactly what you would have seen in real-time. No disappearing signals, no changed duration estimates.
HOW TO USE THE INDICATOR
QUICK START - 3 Steps to Trading:
Step 1: Select Your Trading Style
Open indicator settings → "Quick Setup" section → Trading Style Preset dropdown
Options:
• Auto (Detect from TF) - RECOMMENDED: Automatically configures based on your chart timeframe
• Scalping (1-5m) - For 1-5 minute charts, ultra-fast signals
• Day Trading (15m-1h) - For 15m-1h charts, balanced approach
• Swing Trading (4h-D) - For 4h-Daily charts, trend stability
• Position Trading (D-W) - For Daily-Weekly charts, long-term trends
• Custom - Manual configuration (advanced users only)
Choose "Auto" and you're done - all parameters optimize automatically.
Step 2: Understand the Signals
BUY Signal (Green Triangle Below Price):
• SuperTrend flipped bullish
• Quality score meets minimum threshold (varies by preset)
• Volume confirmation present (if filter enabled)
• Volume momentum rising (if filter enabled)
• duration analysis box shows expected trend duration
SELL Signal (Red Triangle Above Price):
• SuperTrend flipped bearish
• Quality score meets minimum threshold
• Volume confirmation present (if filter enabled)
• Volume momentum rising (if filter enabled)
• duration analysis box shows expected trend duration
Duration Analysis Box:
• Appears at SuperTrend flip (start of new trend)
• Shows median, average, and range duration estimates
• Extends to estimated endpoint based on historical data visually
• Updates mode-specific intelligence (Simple/Standard/Advanced)
Step 3: Use the Dashboard for Context
Dashboard (top-right corner) shows real-time metrics:
• Row 1 - Quality Score: Current setup rating (0-70)
• Row 2 - SuperTrend: Direction and current level
• Row 3 - Volume: Status (Spike/High/Normal/Low) with color
• Row 4 - Volatility: State (Expanding/Rising/Stable/Contracting)
• Row 5 - Volume Momentum: Ratio and trend
• Row 6 - Duration Statistics: Accuracy metrics and track record
Every cell has detailed tooltip - hover for full explanations.
SIGNAL INTERPRETATION BY QUALITY SCORE:
Excellent Setup (60-70 points):
• Quality Score: 60-70
• Volume: Spike or High
• Volatility: Expanding
• Volume Momentum: Strong (1.2x+)
• MTF Confluence (if enabled): 5-6/6
• Action: Primary trade - maximum position size (within risk limits)
• Statistical reliability: Highest - duration estimates most accurate
Strong Setup (45-59 points):
• Quality Score: 45-59
• Volume: High or Above Average
• Volatility: Rising
• Volume Momentum: Rising (1.0-1.2x)
• MTF Confluence (if enabled): 3-4/6
• Action: Standard trade - normal position size
• Statistical reliability: Good - duration estimates reliable
Good Setup (30-44 points):
• Quality Score: 30-44
• Volume: Above Average
• Volatility: Stable or Rising
• Volume Momentum: Neutral to Rising
• MTF Confluence (if enabled): 3-4/6
• Action: Cautious trade - reduced position size, wait for additional confirmation
• Statistical reliability: Moderate - duration estimates less certain
Weak Setup (Below 30 points):
• Quality Score: Below 30
• Volume: Low or Normal
• Volatility: Contracting or Stable
• Volume Momentum: Weak
• MTF Confluence (if enabled): 1-2/6
• Action: Pass or wait for improvement
• Statistical reliability: Low - duration estimates unreliable
USING duration analysis boxES FOR TRADE MANAGEMENT:
Entry Timing:
• Enter on SuperTrend flip (signal bar close)
• duration analysis box appears simultaneously
• Note the median duration - this is your expected hold time
Profit Targets:
• Conservative: Use MEDIAN duration as profit target (50% probability)
• Moderate: Use AVERAGE duration (mean of similar trends)
• Aggressive: Aim for MAX duration from range (best historical outcome)
Position Management:
• Scale out at median duration (take partial profits)
• Trail stop as trend extends beyond median
• Full exit at average duration or SuperTrend flip (whichever comes first)
• Re-evaluate if trend exceeds estimated range
analysis mode Selection:
• Simple: Clean trending markets, beginners, minimal complexity
• Standard: Most markets, most traders (recommended default)
• Advanced: Volatile markets, complex instruments, experienced traders seeking highest accuracy
Asset Type Configuration (Advanced Mode):
If using Advanced analysis mode, configure Asset Type for optimal accuracy:
• Small Cap: Stocks under $2B market cap, low liquidity
• Biotech / Speculative: Clinical-stage pharma, penny stocks, high-risk
• Blue Chip / Large Cap: S&P 500, mega-cap tech, stable large companies
• Tech Growth: High-growth tech (TSLA, NVDA, growth SaaS)
• Dividend / Value: Dividend aristocrats, value stocks, utilities
• Cyclical: Energy, materials, industrials (macro-driven)
• Crypto / High Volatility: Bitcoin, altcoins, highly volatile assets
Correct asset type selection improves Statistical accuracy by 15-20%.
RISK MANAGEMENT GUIDELINES:
1. Stop Loss Placement:
Long positions:
• Place stop below recent swing low OR
• Place stop below SuperTrend level (whichever is tighter)
• Use 1-2 ATR distance as guideline
• Recommended: SuperTrend level (built-in volatility adjustment)
Short positions:
• Place stop above recent swing high OR
• Place stop above SuperTrend level (whichever is tighter)
• Use 1-2 ATR distance as guideline
• Recommended: SuperTrend level
2. Position Sizing by Quality Score:
• Excellent (60-70): Maximum position size (2% risk per trade)
• Strong (45-59): Standard position size (1.5% risk per trade)
• Good (30-44): Reduced position size (1% risk per trade)
• Weak (Below 30): Pass or micro position (0.5% risk - learning trades only)
3. Exit Strategy Options:
Option A - Statistical Duration-Based Exit:
• Exit at median estimated duration (conservative)
• Exit at average estimated duration (moderate)
• Trail stop beyond average duration (aggressive)
Option B - Signal-Based Exit:
• Exit on opposite signal (SELL after BUY, or vice versa)
• Exit on SuperTrend flip (trend reversal)
• Exit if quality score drops below 30 mid-trend
Option C - Hybrid (Recommended):
• Take 50% profit at median estimated duration
• Trail stop on remaining 50% using SuperTrend as trailing level
• Full exit on SuperTrend flip or quality collapse
4. Trade Filtering:
For higher win-rate (fewer trades, better quality):
• Increase minimum quality score (try 60 for swing, 50 for day trading)
• Enable volume momentum filter (ensure institutional participation)
• Require higher MTF confluence (5-6/6 alignment)
• Use Advanced analysis mode with appropriate asset type
For more opportunities (more trades, lower quality threshold):
• Decrease minimum quality score (40 for day trading, 35 for scalping)
• Disable volume momentum filter
• Lower MTF confluence requirement
• Use Simple or Standard analysis mode
SETTINGS OVERVIEW
Quick Setup Section:
• Trading Style Preset: Auto / Scalping / Day Trading / Swing / Position / Custom
Dashboard & Display:
• Show Dashboard (ON/OFF)
• Dashboard Position (9 options: Top/Middle/Bottom + Left/Center/Right)
• Text Size (Auto/Tiny/Small/Normal/Large/Huge)
• Show Ribbon Fill (ON/OFF)
• Show SuperTrend Line (ON/OFF)
• Bullish Color (default: Green)
• Bearish Color (default: Red)
• Show Entry Labels - BUY/SELL signals (ON/OFF)
• Show Info Labels - Volume events (ON/OFF)
• Label Size (Auto/Tiny/Small/Normal/Large/Huge)
Supertrend Configuration:
• ATR Length (default varies by preset: 7-21)
• ATR Multiplier Base (default varies by preset: 2.0-4.0)
• Use Adaptive Multiplier (ON/OFF) - Dynamic 0.8x-1.2x adjustment
• Smoothing Factor (0.0-0.5) - EMA smoothing applied to bands
• Neutral Bars After Flip (0-10) - Hide ST immediately after flip
Volume Momentum:
• Enable Volume Momentum Filter (ON/OFF)
• Fast Period (default varies by preset: 3-20)
• Slow Period (default varies by preset: 10-50)
Volume Analysis:
• Volume MA Length (default varies by preset: 10-50)
• High Volume Threshold (default: 1.5x)
• Spike Threshold (default: 2.5x)
• Low Volume Threshold (default: 0.7x)
Quality Filters:
• Minimum Quality Score (0-70, varies by preset)
• Require Volume Confirmation (ON/OFF)
Trend Duration Analysis:
• Show Duration Analysis (ON/OFF) - Display duration analysis boxes
• analysis mode - Simple / Standard / Advanced
• Asset Type - 7 options (Small Cap, Biotech, Blue Chip, Tech Growth, Dividend, Cyclical, Crypto)
• Use Exponential Weighting (ON/OFF) - Recent trends weighted more
• Decay Factor (0.5-0.99) - How much more recent trends matter
• Structure Lookback (3-30) - Pivot detection period for support/resistance
• Proximity Threshold (xATR) - How close to level qualifies as "near"
• Enable Error Learning (ON/OFF) - System learns from estimation errors
• Memory Depth (3-20) - How many past errors to remember
Box Visual Settings:
• duration analysis box Border Color
• duration analysis box Background Color
• duration analysis box Text Color
• duration analysis box Border Width
• duration analysis box Transparency
Multi-Timeframe (Optional Feature):
• Enable MTF Confluence (ON/OFF)
• Minimum Alignment Required (0-6)
• Individual timeframe enable/disable toggles
• Custom timeframe selection options
All preset configurations override manual inputs except when "Custom" is selected.
ADVANCED FEATURES
1. Scalpel Mode (Optional)
Advanced pullback entry system that waits for healthy retracements within established trends before signaling entry:
• Monitors price distance from SuperTrend levels
• Requires pullback to configurable range (default: 30-50%)
• Ensures trend remains intact before entry signal
• Reduces whipsaw and false breakouts
• Inspired by Mark Minervini's VCP pullback entries
Best for: Swing traders and day traders seeking precision entries
Scalpers: Consider disabling for faster entries
2. Error Learning System (Advanced analysis mode Only)
The system learns from its own estimation errors:
• Tracks last 10-20 completed duration estimates (configurable memory depth)
• Calculates error ratio for each: estimated duration / Actual Duration
• If system consistently over-estimates: Applies negative correction (-15%)
• If system consistently under-estimates: Applies positive correction (+15%)
• Adapts to current market regime automatically
This self-correction mechanism improves accuracy over time as the system gathers more data on your specific symbol and timeframe.
3. Regime Detection (Advanced analysis mode Only)
Automatically detects whether market is in trending or choppy regime:
• Compares last 3 trends to historical average
• Recent trends 20%+ longer → Trending regime (+20% to estimates)
• Recent trends 20%+ shorter → Choppy regime (-20% to estimates)
• Applied separately to bullish and bearish trends
Helps duration estimates adapt to changing market conditions without manual intervention.
4. Exponential Weighting
Option to weight recent trends more heavily than distant history:
• Default decay factor: 0.9
• Recent trends get higher weight in statistical calculations
• Older trends gradually decay in importance
• Rationale: Recent market behavior more relevant than old data
• Can be disabled for equal weighting
5. Backtest Statistics
System backtests its own duration estimates using historical data:
• Walks through past trends chronologically
• Calculates what duration estimate WOULD have been at each flip
• Compares to actual duration that occurred
• Displays accuracy metrics in duration analysis boxes and dashboard
• Helps assess statistical reliability on your specific chart
Note: Backtest uses only data available AT THE TIME of each historical flip (no lookahead bias).
TECHNICAL SPECIFICATIONS
• Pine Script Version: v6
• Indicator Type: Overlay (draws on price chart)
• Max Boxes: 500 (for duration analysis box storage)
• Max Bars Back: 5000 (for comprehensive historical analysis)
• Security Calls: 1 (for MTF if enabled - optimized)
• Repainting: NO - All signals and duration estimates confirmed on bar close
• Lookahead Bias: NO - All HTF data properly offset, all duration estimates use only historical data
• Real-time Updates: YES - Dashboard and quality scores update live
• Alert Capable: YES - Both automatic alerts and customizable alert conditions
• Multi-Symbol: Works on stocks, crypto, forex, futures, indices
Performance Optimization:
• Conditional calculations (duration analysis can be disabled to reduce load)
• Efficient array management (circular buffers for trend storage)
• Streamlined gradient rendering (26 layers, can be toggled off)
• Smart label cooldown system (prevents label spam)
• Optimized similarity matching (analyzes only relevant trends)
Data Requirements:
• Minimum 50-100 bars for initial duration analysis (builds historical database)
• Optimal: 500+ bars for robust statistical analysis
• Longer history = more accurate duration estimates
• Works on any timeframe from 1 minute to monthly
KNOWN LIMITATIONS
• Trending Markets Only: Performs best in clear trends. May generate false signals in choppy/sideways markets (use quality score filtering and regime detection to mitigate)
• Lagging Nature: Like all trend-following systems, signals occur AFTER trend establishment, not at exact tops/bottoms. Use duration analysis boxes to set realistic profit targets.
• Initial Learning Period: Duration analysis system requires 10-15 completed trends to build reliable historical database. Early duration estimates less accurate (first few weeks on new symbol/timeframe).
• Visual Load: 26-layer gradient ribbon may slow performance on older devices. Disable ribbon if experiencing lag.
• Statistical accuracy Variables: Duration estimates are statistical estimates, not guarantees. Accuracy varies by:
- Market regime (trending vs choppy)
- Asset volatility characteristics
- Quality of historical pattern matches
- Timeframe traded (higher TF = more reliable)
• Not Best Suitable For:
- Ultra-short-term scalping (sub-1-minute charts)
- Mean-reversion strategies (designed for trend-following)
- Range-bound trading (requires trending conditions)
- News-driven spikes (estimates based on technical patterns, not fundamentals)
FREQUENTLY ASKED QUESTIONS
Q: Does this indicator repaint?
A: Absolutely not. All signals, duration analysis boxes, labels, and alerts use barstate.isconfirmed checks. They only appear after the bar closes. What you see in history is exactly what you would have seen in real-time. Zero repaint guarantee.
Q: How accurate are the trend duration estimates?
A: Accuracy varies by mode, market conditions, and historical data quality:
• Simple mode: 60-70% accuracy (within ±20% of actual duration)
• Standard mode: 70-80% accuracy (within ±20% of actual duration)
• Advanced mode: 75-85% accuracy (within ±20% of actual duration)
Best accuracy achieved on:
• Higher timeframes (4H, Daily, Weekly)
• Trending markets (not choppy/sideways)
• Assets with consistent behavior (Blue Chip, Large Cap)
• After 20+ historical trends analyzed (builds robust database)
Remember: All duration estimates are statistical calculations based on historical patterns, not guarantees.
Q: Which analysis mode should I use?
A:
• Simple: Beginners, clean trending markets, want minimal complexity
• Standard: Most traders, general market conditions (RECOMMENDED DEFAULT)
• Advanced: Experienced traders, volatile/complex markets (biotech, small-cap, crypto), seeking maximum accuracy
Advanced mode requires correct Asset Type configuration for optimal results.
Q: What's the difference between the trading style presets?
A: Each preset optimizes ALL parameters for a specific trading approach:
• Scalping: Ultra-sensitive (ATR 7, Mult 2.0), more signals, shorter holds
• Day Trading: Balanced (ATR 10, Mult 2.5), moderate signals, intraday holds
• Swing Trading: Stable (ATR 14, Mult 3.0), fewer signals, multi-day holds
• Position Trading: Very stable (ATR 21, Mult 4.0), rare signals, week/month holds
Auto mode automatically selects based on your chart timeframe.
Q: Should I use Auto mode or manually select a preset?
A: Auto mode is recommended for most traders. It automatically matches settings to your timeframe and re-optimizes if you switch charts. Only use manual preset selection if:
• You want scalping settings on a 15m chart (overriding auto-detection)
• You want swing settings on a 1h chart (more conservative than auto would give)
• You're testing different approaches on same timeframe
Q: Can I use this for scalping and day trading?
A: Absolutely! The preset system is specifically designed for all trading styles:
• Select "Scalping (1-5m)" for 1-5 minute charts
• Select "Day Trading (15m-1h)" for 15m-1h charts
• Or use "Auto" mode and it configures automatically
Volume momentum filter is auto-disabled in Scalping mode for faster signals.
Q: What is Volume Momentum and why does it matter?
A: Volume Momentum compares short-term volume (fast MA) to long-term volume (slow MA). It answers: "Is money flowing into this asset faster now than historically?"
Why it matters:
• Volume often leads price (early warning system)
• Confirms institutional participation (smart money)
• No lag like price-based indicators
• More intuitive than complex mathematical filters
When the ratio is above 1.2, you have strong evidence that institutions are accumulating (bullish) or distributing (bearish).
Q: How do I set up alerts?
A: Two options:
Option 1 - Automatic Alerts:
1. Right-click on chart → Add Alert
2. Condition: Select this indicator
3. Choose "Any alert() function call"
4. Configure notification method (app, email, webhook)
5. You'll receive detailed alerts on every BUY and SELL signal
Option 2 - Customizable Alert Conditions:
1. Right-click on chart → Add Alert
2. Condition: Select this indicator
3. You'll see three options in dropdown:
- "BUY Signal" (long signals only)
- "SELL Signal" (short signals only)
- "ANY Signal" (both BUY and SELL)
4. Choose desired option and customize message template
5. Uses TradingView placeholders: {{ticker}}, {{close}}, {{time}}, etc.
All alerts fire only on confirmed bar close (no repaint).
Q: What is Scalpel Mode and should I use it?
A: Scalpel Mode waits for healthy pullbacks within established trends before signaling entry. It reduces whipsaws and improves entry timing.
Recommended ON for:
• Swing traders (want precision entries on pullbacks)
• Day traders (willing to wait for better prices)
• Risk-averse traders (prefer fewer but higher-quality entries)
Recommended OFF for:
• Scalpers (need immediate entries, can't wait for pullbacks)
• Momentum traders (want to enter on breakout, not pullback)
• Aggressive traders (prefer more opportunities over precision)
Q: Why do some duration estimates show wider ranges than others?
A: Range width reflects historical trend variability:
• Narrow range: Similar historical trends had consistent durations (high confidence)
• Wide range: Similar historical trends had varying durations (lower confidence)
Wide ranges often occur:
• Early in analysis (fewer historical trends to learn from)
• In volatile/choppy markets (inconsistent trend behavior)
• On lower timeframes (more noise, less consistency)
The median and average still provide useful targets even when range is wide.
Q: Can I customize the dashboard position and appearance?
A: Yes! Dashboard settings include:
• Position: 9 options (Top/Middle/Bottom + Left/Center/Right)
• Text Size: Auto, Tiny, Small, Normal, Large, Huge
• Show/Hide: Toggle entire dashboard on/off
Choose position that doesn't overlap important price action on your specific chart.
Q: Which timeframe should I trade on?
A: Depends on your trading style and time availability:
• 1-5 minute: Active scalping, requires constant monitoring
• 15m-1h: Day trading, check few times per session
• 4h-Daily: Swing trading, check once or twice daily
• Daily-Weekly: Position trading, check weekly
General principle: Higher timeframes produce:
• Fewer signals (less frequent)
• Higher quality setups (stronger confirmations)
• More reliable duration estimates (better statistical data)
• Less noise (clearer trends)
Start with Daily chart if new to trading. Move to lower timeframes as you gain experience.
Q: Does this work on all markets (stocks, crypto, forex)?
A: Yes, it works on all markets with trending characteristics:
Excellent for:
• Stocks (especially growth and momentum names)
• Crypto (BTC, ETH, major altcoins)
• Futures (indices, commodities)
• Forex majors (EUR/USD, GBP/USD, etc.)
Best results on:
• Trending markets (not range-bound)
• Liquid instruments (tight spreads, good fills)
• Volatile assets (clear trend development)
Less effective on:
• Range-bound/sideways markets
• Ultra-low volatility instruments
• Illiquid small-caps (use caution)
Configure Asset Type (in Advanced analysis mode) to match your instrument for best accuracy.
Q: How many signals should I expect per day/week?
A: Highly variable based on:
By Timeframe:
• 1-5 minute: 5-15 signals per session
• 15m-1h: 2-5 signals per day
• 4h-Daily: 2-5 signals per week
• Daily-Weekly: 1-2 signals per month
By Market Volatility:
• High volatility = more SuperTrend flips = more signals
• Low volatility = fewer flips = fewer signals
By Quality Filter:
• Higher threshold (60-70) = fewer but better signals
• Lower threshold (30-40) = more signals, lower quality
By Volume Momentum Filter:
• Enabled = Fewer signals (only volume-confirmed)
• Disabled = More signals (all SuperTrend flips)
Adjust quality threshold and filters to match your desired signal frequency.
Q: What's the difference between entry labels and info labels?
A:
Entry Labels (BUY/SELL):
• Your primary trading signals
• Based on SuperTrend flip + all confirmations (quality, volume, momentum)
• Include quality score and confirmation icons
• These are actionable entry points
Info Labels (Volume Spike):
• Additional market context
• Show volume events that may support or contradict trend
• 8-bar cooldown to prevent spam
• NOT necessarily entry points - contextual information only
Control separately: Can show entry labels without info labels (recommended for clean charts).
Q: Can I combine this with other indicators?
A: Absolutely! This works well with:
• RSI: For divergences and overbought/oversold conditions
• Support/Resistance: Confluence with key levels
• Fibonacci Retracements: Pullback targets in Scalpel Mode
• Price Action Patterns: Flags, pennants, cup-and-handle
• MACD: Additional momentum confirmation
• Bollinger Bands: Volatility context
This indicator provides trend direction and duration estimates - complement with other tools for entry refinement and additional confluence.
Q: Why did I get a low-quality signal? Can I filter them out?
A: Yes! Increase the Minimum Quality Score in settings.
If you're seeing signals with quality below your preference:
• Day Trading: Set minimum to 50
• Swing Trading: Set minimum to 60
• Position Trading: Set minimum to 70
Only signals meeting the threshold will appear. This reduces frequency but improves win-rate.
Q: How do I interpret the MTF Confluence count?
A: Shows how many of 6 timeframes agree with current trend:
• 6/6 aligned: Perfect agreement (extremely rare, highest confidence)
• 5/6 aligned: Very strong alignment (high confidence)
• 4/6 aligned: Good alignment (standard quality setup)
• 3/6 aligned: Moderate alignment (acceptable)
• 2/6 aligned: Weak alignment (caution)
• 1/6 aligned: Very weak (likely counter-trend)
Higher confluence typically correlates with longer, stronger trends. However, MTF analysis is optional - you can disable it and rely solely on quality scoring.
Q: Is this suitable for beginners?
A: Yes, but requires foundational knowledge:
You should understand:
• Basic trend-following concepts (higher highs, higher lows)
• Risk management principles (position sizing, stop losses)
• How to read candlestick charts
• What volume and volatility mean
Beginner-friendly features:
• Auto preset mode (zero configuration)
• Quality scoring (tells you signal strength)
• Dashboard tooltips (hover for explanations)
• duration analysis boxes (visual profit targets)
Recommended for beginners:
1. Start with "Auto" or "Swing Trading" preset on Daily chart
2. Use Standard Analysis Mode (not Advanced)
3. Set minimum quality to 60 (fewer but better signals)
4. Paper trade first for 2-4 weeks
5. Study methodology references (Minervini, O'Neil, Zanger)
Q: What is the Asset Type setting and why does it matter?
A: Asset Type (in Advanced analysis mode) adjusts duration estimates based on volatility characteristics:
• Small Cap: Explosive moves, extended trends (+30-40%)
• Biotech / Speculative: Parabolic potential, news-driven (+40%)
• Blue Chip / Large Cap: Baseline, steady trends (0% adjustment)
• Tech Growth: Momentum-driven, longer trends (+20%)
• Dividend / Value: Slower, grinding trends (-20%)
• Cyclical: Macro-driven, variable (±10%)
• Crypto / High Volatility: Parabolic potential (+30%)
Correct configuration improves Statistical accuracy by 15-20%. Using Blue Chip settings on a biotech stock may underestimate trend length (you'll exit too early).
Q: Can I backtest this indicator?
A: Yes! TradingView's Strategy Tester works with this indicator's signals.
To backtest:
1. Note the entry conditions (SuperTrend flip + quality threshold + filters)
2. Create a strategy script using same logic
3. Run Strategy Tester on historical data
Additionally, the indicator includes BUILT-IN duration estimate validation:
• System backtests its own duration estimates
• Shows accuracy metrics in dashboard and duration analysis boxes
• Helps assess reliability on your specific symbol/timeframe
Q: Why does Volume Momentum auto-disable in Scalping mode?
A: Scalping requires ultra-fast entries to catch quick moves. Volume Momentum filter adds friction by requiring volume confirmation before signaling, which can cause missed opportunities in rapid scalping.
Scalping preset is optimized for speed and frequency - the filter is counterproductive for that style. It remains enabled for Day Trading, Swing Trading, and Position Trading presets where patience improves results.
You can manually enable it in Custom mode if desired.
Q: How much historical data do I need for accurate duration estimates?
A:
Minimum: 50-100 bars (indicator will function but duration estimates less reliable)
Recommended: 500+ bars (robust statistical database)
Optimal: 1000+ bars (maximum Statistical accuracy)
More history = more completed trends = better pattern matching = more accurate duration estimates.
New symbols or newly-switched timeframes will have lower Statistical accuracy initially. Allow 2-4 weeks for the system to build historical database.
IMPORTANT DISCLAIMERS
No Guarantee of Profit:
This indicator is an educational tool and does not guarantee any specific trading results. All trading involves substantial risk of loss. Duration estimates are statistical calculations based on historical patterns and are not guarantees of future performance.
Past Performance:
Historical backtest results and Statistical accuracy statistics do not guarantee future performance. Market conditions change constantly. What worked historically may not work in current or future markets.
Not Financial Advice:
This indicator provides technical analysis signals and statistical duration estimates only. It is not financial, investment, or trading advice. Always consult with a qualified financial advisor before making investment decisions.
Risk Warning:
Trading stocks, options, futures, forex, and cryptocurrencies involves significant risk. You can lose all of your invested capital. Never trade with money you cannot afford to lose. Only risk capital you can lose without affecting your lifestyle.
Testing Required:
Always test this indicator on a demo account or with paper trading before risking real capital. Understand how it works in different market conditions. Verify Statistical accuracy on your specific instruments and timeframes before trusting it with real money.
User Responsibility:
You are solely responsible for your trading decisions. The developer assumes no liability for trading losses, incorrect duration estimates, software errors, or any other damages incurred while using this indicator.
Statistical Estimation Limitations:
Trend Duration estimates are statistical estimates based on historical pattern matching. They are NOT guarantees. Actual trend durations may differ significantly from duration estimates due to unforeseen news events, market regime changes, or lack of historical precedent for current conditions.
CREDITS & ACKNOWLEDGMENTS
Methodology Inspiration:
• Mark Minervini - Volatility Contraction Pattern (VCP) concepts and pullback entry techniques
• William O'Neil - Volume analysis principles and CANSLIM institutional buying patterns
• Dan Zanger - Momentum breakout strategies and volatility expansion entries
Technical Components:
• SuperTrend calculation - Classic ATR-based trend indicator (public domain)
• Statistical analysis - Standard median, average, range calculations
• k-Nearest Neighbors - Classic machine learning similarity matching concept
• Multi-timeframe analysis - Standard request.security implementation in Pine Script
For questions, feedback, or support, please comment below or send a private message.
Happy Trading!
EP CPR Future CPR + 4 MA
1. CPR Trend Direction(Bias):
Bullish: If the current day's price is trading above the TC, it suggests a strong bullish trend where the CPR acts as a support zone.
Bearish: If the current day's price is trading below the BC, it suggests a strong bearish trend where the CPR acts as a resistance zone.
Range-Bound/Consolidation: If the price is trading within the CPR lines, it indicates a lack of clear directional bias and suggests a likely sideways or accumulation phase.
2. Moving average Trend Identification
Uptrend: If the price is above a moving average (and the MA line is sloping up), it confirms a bullish trend.
Downtrend: If the price is below a moving average (and the MA line is sloping down), it confirms a bearish trend.
Crossovers (Trading Signals)
A popular strategy involves using two moving averages—a short-term MA (e.g., 50-period) and a long-term MA (e.g., 200-period).
Golden Cross (Bullish Signal): Occurs when the shorter-term MA crosses above the longer-term MA.
Death Cross (Bearish Signal): Occurs when the shorter-term MA crosses below the longer-term MA.
Lorentzian Harmonic Flow - Adaptive ML⚡ LORENTZIAN HARMONIC FLOW — ADAPTIVE ML COMPLETE SYSTEM
THEORETICAL FOUNDATION: TEMPORAL RELATIVITY MEETS MACHINE LEARNING
The Lorentzian Harmonic Flow Adaptive ML system represents a paradigm shift in technical analysis by addressing a fundamental limitation that plagues traditional indicators: they assume time flows uniformly across all market conditions. In reality, markets experience time compression during volatile breakouts and time dilation during consolidation. A 50-period moving average calculated during a quiet overnight session captures vastly different market information than the same calculation during a high-volume news event.
This indicator solves this problem through Lorentzian spacetime modeling , borrowed directly from Einstein's special relativity. By calculating a dynamic gamma factor (γ) that measures market velocity relative to a volatility-based "speed of light," every calculation adapts its effective lookback period to the market's intrinsic clock. Combined with a dual-memory architecture, multi-regime detection, and Bayesian strategy selection, this creates a system that genuinely learns which approaches work in which market conditions.
CRITICAL DISTINCTION: TRUE ADAPTIVE LEARNING VS STATIC CLASSIFICATION
Before diving into the system architecture, it's essential to understand how this indicator fundamentally differs from traditional "Lorentzian" implementations, particularly the well-known Lorentzian Classification indicator.
THE ORIGINAL LORENTZIAN CLASSIFICATION APPROACH:
The pioneering Lorentzian Classification indicator (Jdehorty, 2022) introduced the financial community to Lorentzian distance metrics for pattern matching. However, it used offline training methodology :
• External Training: Required Python scripts or external ML tools to train the model on historical data
• Static Model: Once trained, the model parameters remained fixed
• No Real-Time Learning: The indicator classified patterns but didn't learn from outcomes
• Look-Ahead Bias Risk: Offline training could inadvertently use future data
• Manual Retraining: To adapt to new market conditions, users had to retrain externally and reload parameters
This was groundbreaking for bringing ML concepts to Pine Script, but it wasn't truly adaptive. The model was a snapshot—trained once, deployed, static.
THIS SYSTEM: TRUE ONLINE LEARNING
The Lorentzian Harmonic Flow Adaptive ML system represents a complete architectural departure :
✅ FULLY SELF-CONTAINED:
• Zero External Dependencies: No Python scripts, no external training tools, no data exports
• 100% Pine Script: Entire learning pipeline executes within TradingView
• One-Click Deployment: Load indicator, it begins learning immediately
• No Manual Configuration: System builds its own training data in real-time
✅ GENUINE FORWARD-WALK LEARNING:
• Real-Time Adaptation: Every trade outcome updates the model
• Forward-Only Logic: System uses only past confirmed data—zero look-ahead bias
• Continuous Evolution: Parameters adapt bar-by-bar based on rolling performance
• Regime-Specific Memory: Learns which patterns work in which conditions independently
✅ GETS BETTER WITH TIME:
• Week 1: Bootstrap mode—gathering initial data across regimes
• Month 2-3: Statistical significance emerges, parameter adaptation begins
• Month 4+: Mature learning, regime-specific optimization, confident selection
• Year 2+: Deep pattern library, proven parameter sets, robust to regime shifts
✅ NO RETRAINING REQUIRED:
• Automatic Adaptation: When market structure changes, system detects via performance degradation
• Memory Refresh: Old patterns naturally decay, new patterns replace them
• Parameter Evolution: Thresholds and multipliers adjust to current conditions
• Regime Awareness: If new regime emerges, enters bootstrap mode automatically
THE FUNDAMENTAL DIFFERENCE:
Traditional Lorentzian Classification:
"Here are patterns from the past. Current state matches pattern X, which historically preceded move Y. Signal fired."
→ Static knowledge, fixed rules, periodic retraining required
LHF Adaptive ML:
"In Trending Bull regime, Strategy B has 58% win rate and 1.4 Sharpe over last 30 trades. In High Vol Range, Strategy C performs better with 61% win rate and 1.8 Sharpe. Current state is Trending Bull, so I select Strategy B. If Strategy B starts failing, I'll adapt parameters or switch strategies. I'm learning which patterns matter in which contexts, and I improve every trade."
→ Dynamic learning, contextual adaptation, self-improving system
WHY THIS MATTERS:
Markets are non-stationary. A model trained on 2023 data may fail in 2024 when Fed policy shifts, volatility regime changes, or market structure evolves. Static models require constant human intervention—retraining, re-optimization, parameter updates.
This system learns continuously . It doesn't need you to tell it when markets changed. It discovers regime shifts through performance feedback, adapts parameters accordingly, and rebuilds its pattern library organically. The system running in Month 12 is fundamentally smarter than the system in Month 1—not because you retrained it, but because it learned from 1,000+ real outcomes.
This is the difference between pattern recognition (static ML) and reinforcement learning (adaptive ML). One classifies, the other learns and improves.
PART 1: LORENTZIAN TEMPORAL DYNAMICS
Markets don't experience time uniformly. During explosive volatility, price can compress weeks of movement into minutes. During consolidation, time dilates. Traditional indicators ignore this, using fixed periods regardless of market state.
The Lorentzian approach models market time using the Lorentz factor from special relativity:
γ = 1 / √(1 - v²/c²)
Where:
• v (velocity): Trend momentum normalized by ATR, calculated as (close - close ) / (N × ATR)
• c (speed limit): Realized volatility + volatility bursts, multiplied by c_multiplier parameter
• γ (gamma): Time dilation factor that compresses or expands effective lookback periods
When trend velocity approaches the volatility "speed limit," gamma spikes above 1.0, compressing time. Every calculation length becomes: base_period / γ. This creates shorter, more responsive periods during explosive moves and longer, more stable periods during quiet consolidation.
The system raises gamma to an optional power (gamma_power parameter) for fine control over compression strength, then applies this temporal scaling to every calculation in the indicator. This isn't metaphor—it's quantitative adaptation to the market's intrinsic clock.
PART 2: LORENTZIAN KERNEL SMOOTHING
Traditional moving averages use uniform weights (SMA) or exponential decay (EMA). The Lorentzian kernel uses heavy-tailed weighting:
K(distance, γ) = 1 / (1 + (distance/γ)²)
This Cauchy-like distribution gives more influence to recent extremes than Gaussian assumptions suggest, capturing the fat-tailed nature of financial returns. For any calculation requiring smoothing, the system loops through historical bars, computes Lorentzian kernel weights based on temporal distance and current gamma, then produces weighted averages.
This creates adaptive smoothing that responds to local volatility structure rather than imposing rigid assumptions about price distribution.
PART 3: HARMONIC FLOW (Multi-Timeframe Momentum)
The core directional signal comes from Harmonic Flow (HFL) , which blends three gamma-compressed Lorentzian smooths:
• Short Horizon: base_period × short_ratio / γ (default: 34 × 0.5 / γ ≈ 17 bars, faster with high γ)
• Mid Horizon: base_period × mid_ratio / γ (default: 34 × 1.0 / γ ≈ 34 bars, anchor timeframe)
• Long Horizon: base_period × long_ratio / γ (default: 34 × 2.5 / γ ≈ 85 bars, structural trend)
Each produces a Lorentzian-weighted smooth, converted to a z-score (distance from smooth normalized by ATR). These z-scores are then weighted-averaged:
HFL = (w_short × z_short + w_mid × z_mid + w_long × z_long) / (w_short + w_mid + w_long)
Default weights (0.45, 0.35, 0.20) favor recent momentum while respecting longer structure. Scalpers can increase short weight; swing traders can emphasize long weight. The result is a directional momentum indicator that captures multi-timeframe flow in compressed time.
From HFL, the system derives:
• Flow Velocity: HFL - HFL (momentum acceleration)
• Flow Acceleration: Second derivative (turning points)
• Temporal Compression Index (TCI): base_period / compressed_length (shows how much time is compressed)
PART 4: DUAL MEMORY ARCHITECTURE
Markets have memory—current conditions resonate with past regimes. But memory operates on two timescales, inspiring this indicator's dual-memory design:
SHORT-TERM MEMORY (STM):
• Capacity: 100 patterns (configurable 50-200)
• Decay Rate: 0.980 (50% weight after ~35 bars)
• Update Frequency: Every 10 bars
• Purpose: Capture current regime's tactical patterns
• Storage: Recent market states with 10-bar forward outcomes
• Analogy: Hippocampus (rapid encoding, fast fade)
LONG-TERM MEMORY (LTM):
• Capacity: 512 patterns (configurable 256-1024)
• Decay Rate: 0.997 (50% weight after ~230 bars)
• Quality Gate: Only high-quality patterns admitted (adaptive threshold per regime)
• Purpose: Strategic pattern library validated across regimes
• Storage: Validated patterns from weeks/months of history
• Analogy: Neocortex (slow consolidation, persistent storage)
Each memory stores 6-dimensional feature vectors:
1. HFL (harmonic flow strength)
2. Flow Velocity (momentum)
3. Flow Acceleration (turning points)
4. Volatility (realized vol EMA)
5. Entropy (market uncertainty)
6. Gamma (time compression state)
Plus the actual outcome (10-bar forward return).
K-NEAREST NEIGHBORS (KNN) PATTERN MATCHING:
When evaluating current market state, the system queries both memories using Lorentzian distance :
distance = Σ (1 - K(|feature_current - feature_memory|, γ))
This calculates similarity across all 6 dimensions using the same Lorentzian kernel, weighted by current gamma. The system finds K nearest neighbors (default: 8), weights each by:
• Similarity: Lorentzian kernel distance
• Age: Exponential decay based on bars since pattern
• Regime: Only patterns from similar regimes count
The weighted average of these neighbors' outcomes becomes the prediction. High-confidence predictions require both high similarity and agreement between multiple neighbors.
REGIME-AWARE BLENDING:
STM and LTM predictions are blended adaptively:
• High Vol Range regime: Trust STM 70% (recent matters in chaos)
• Trending regimes: Trust LTM 70% (structure matters in trends)
• Normal regimes: 50/50 blend
Agreement metric: When STM and LTM strongly disagree, the system flags low confidence—often indicating regime transition or novel market conditions requiring caution.
PART 5: FIVE-REGIME MARKET CLASSIFICATION
Traditional regime detection stops at "trending vs ranging." This system detects five distinct market states using linear regression slope and volatility analysis:
REGIME 0: TRENDING BULL ↗
• Detection: LR slope > trend_threshold (default: 0.3)
• Characteristics: Sustained positive HFL, elevated gamma, low entropy
• Best Strategy: B (Flow Momentum)
• Trading Behavior: Follow momentum, trail stops, pyramid winners
REGIME 1: TRENDING BEAR ↘
• Detection: LR slope < -trend_threshold
• Characteristics: Sustained negative HFL, elevated gamma, low entropy
• Best Strategy: B (Flow Momentum)
• Trading Behavior: Follow momentum short, aggressive exits on reversal
REGIME 2: HIGH VOL RANGE ↔
• Detection: |slope| < threshold AND vol_ratio > vol_expansion_threshold (default: 1.5)
• Characteristics: Oscillating HFL, high gamma spikes, high entropy
• Best Strategies: A (Squeeze Breakout) or C (Memory Pattern)
• Trading Behavior: Fade extremes, tight stops, quick profits
REGIME 3: LOW VOL RANGE —
• Detection: |slope| < threshold AND vol_ratio < vol_expansion_threshold
• Characteristics: Low HFL magnitude, gamma ≈ 1, squeeze conditions
• Best Strategy: A (Squeeze Breakout)
• Trading Behavior: Wait for breakout, wide stops on breakout entry
REGIME 4: TRANSITION ⚡
• Detection: Trend reversal OR volatility spike > 1.5× threshold
• Characteristics: Erratic gamma, high entropy, conflicting signals
• Best Strategy: None (often unfavorable)
• Trading Behavior: Stand aside, wait for clarity
Each regime gets a confidence score (0-1) measuring how clearly defined it is. Low confidence indicates messy, ambiguous conditions.
PART 6: THREE INDEPENDENT TRADING STRATEGIES
Rather than one signal logic, the system implements three distinct approaches:
STRATEGY A: SQUEEZE BREAKOUT
• Logic: Bollinger Bands squeeze release + HFL direction + flow velocity confirmation
• Calculation: Compares BB width to Keltner Channel width; fires when BB expands beyond KC
• Strength Score: 70 + compression_strength × 0.3 (tighter squeeze = higher score)
• Best Regimes: Low Vol Range (3), Transition exit (4→0 or 4→1)
• Pattern: Volatility contraction → directional expansion
• Philosophy: Calm before the storm; compression precedes explosion
STRATEGY B: LORENTZIAN FLOW MOMENTUM
• Logic: Strong HFL (×flow_mult) + positive velocity + gamma > 1.1 + NOT squeezing
• Calculation: |HFL × flow_mult| > 0.12, velocity confirms direction, gamma shows acceleration
• Strength Score: |HFL × flow_mult| × 80 + gamma × 10
• Best Regimes: Trending Bull (0), Trending Bear (1)
• Pattern: Established momentum → acceleration in compressed time
• Philosophy: Trend is friend when spacetime curves
STRATEGY C: MEMORY PATTERN MATCHING
• Logic: Dual KNN prediction > threshold + high confidence + agreement + HFL confirms
• Calculation: |memory_pred| > 0.005, memory_conf > 1.0, agreement > 0.5, HFL direction matches
• Strength Score: |prediction| × 800 × agreement
• Best Regimes: High Vol Range (2), sometimes others with sufficient pattern library
• Pattern: Historical similarity → outcome resonance
• Philosophy: Markets rhyme; learn from validated patterns
Each strategy generates independent strength scores. In multi-strategy mode (enabled by default), the system selects one strategy per regime based on risk-adjusted performance. In weighted mode (multi-strategy disabled), all three fire simultaneously with configurable weights.
PART 7: ADAPTIVE LEARNING & BAYESIAN SELECTION
This is where machine learning meets trading. The system maintains 15 independent performance matrices :
3 strategies × 5 regimes = 15 tracking systems
For each combination, it tracks:
• Trade Count: Number of completed trades
• Win Count: Profitable outcomes
• Total Return: Sum of percentage returns
• Squared Returns: For variance/Sharpe calculation
• Equity Curve: Virtual P&L assuming 10% risk per trade
• Peak Equity: All-time high for drawdown calculation
• Max Drawdown: Peak-to-trough decline
RISK-ADJUSTED SCORING:
For current regime, the system scores each strategy:
Sharpe Ratio: (mean_return / std_dev) × √252
Calmar Ratio: total_return / max_drawdown
Win Rate: wins / trades
Combined Score = 0.6 × Sharpe + 0.3 × Calmar + 0.1 × Win_Rate
The strategy with highest score is selected. This is similar to Thompson Sampling (multi-armed bandits) but uses deterministic selection rather than probabilistic sampling due to Pine Script limitations.
BOOTSTRAP MODE (Critical for Understanding):
For the first min_regime_samples trades (default: 10) in each regime:
• Status: "🔥 BOOTSTRAP (X/10)" displayed in dashboard
• Behavior: All signals allowed (gathering data)
• Regime Filter: Disabled (can't judge with insufficient data)
• Purpose: Avoid cold-start problem, build statistical foundation
After reaching threshold:
• Status: "✅ FAVORABLE" (score > 0.5) or "⚠️ UNFAVORABLE" (score ≤ 0.5)
• Behavior: Only trade favorable regimes (if enable_regime_filter = true)
• Learning: Parameters adapt based on outcomes
This solves a critical problem: you can't know which strategy works in a regime without data, but you can't get data without trading. Bootstrap mode gathers initial data safely, then switches to selective mode once statistical confidence emerges.
PARAMETER ADAPTATION (Per Regime):
Three parameters adapt independently for each regime based on outcomes:
1. SIGNAL QUALITY THRESHOLD (30-90):
• Starts: base_quality_threshold (default: 60)
• Adaptation:
Win Rate < 45% → RAISE threshold by learning_rate × 10 (be pickier)
Win Rate > 55% → LOWER threshold by learning_rate × 5 (take more)
• Effect: System becomes more selective in losing regimes, more aggressive in winning regimes
2. LTM QUALITY GATE (0.2-0.8):
• Starts: 0.4 (if adaptive gate enabled)
• Adaptation:
Sharpe < 0.5 → RAISE gate by learning_rate (demand better patterns)
Sharpe > 1.5 → LOWER gate by learning_rate × 0.5 (accept more patterns)
• Effect: LTM fills with high-quality patterns from winning regimes
3. FLOW MULTIPLIER (0.5-2.0):
• Starts: 1.0
• Adaptation:
Strong win (+2%+) → MULTIPLY by (1 + learning_rate × 0.1)
Strong loss (-2%+) → MULTIPLY by (1 - learning_rate × 0.1)
• Effect: Amplifies signal strength in profitable regimes, dampens in unprofitable
Each regime evolves independently. Trending Bull might develop threshold=55, gate=0.35, mult=1.3 while High Vol Range develops threshold=70, gate=0.50, mult=0.9.
PART 8: SHADOW PORTFOLIO VALIDATION
To validate learning objectively, the system runs three virtual portfolios :
Shadow Portfolio A: Trades only Strategy A signals
Shadow Portfolio B: Trades only Strategy B signals
Shadow Portfolio C: Trades only Strategy C signals
When any signal fires:
1. Open virtual position for corresponding strategy
2. On exit, calculate P&L (10% risk per trade)
3. Update equity, win count, profit factor
Dashboard displays:
• Equity: Current virtual balance (starts $10,000)
• Win%: Overall win rate across all regimes
• PF: Profit Factor (gross_profit / gross_loss)
This transparency shows which strategies actually perform, validates the selection logic, and prevents overfitting. If Shadow C shows $12,500 equity while A and B show $9,800, it confirms Strategy C's edge.
PART 9: HISTORICAL PRE-TRAINING
The system includes historical pre-training to avoid cold-start:
On Chart Load (if enabled):
1. Scan past pretrain_bars (default: 200)
2. Calculate historical HFL, gamma, velocity, acceleration, volatility, entropy
3. Compute 10-bar forward returns as outcomes
4. Populate STM with recent patterns
5. Populate LTM with high-quality patterns (quality > 0.4)
Effect:
• Without pre-training: Memories empty, no predictions for weeks, pure bootstrap
• With pre-training: System starts with pattern library, predictions from day one
Pre-training uses only past data (no future peeking) and fills memories with validated outcomes. This dramatically accelerates learning without compromising integrity.
PART 10: COMPREHENSIVE INPUT SYSTEM
The indicator provides 50+ inputs organized into logical groups. Here are the key parameters and their market-specific guidance:
🧠 ADAPTIVE LEARNING SYSTEM:
Enable Adaptive Learning (true/false):
• Function: Master switch for regime-specific strategy selection and parameter adaptation
• Enabled: System learns which strategies work in which regimes (recommended)
• Disabled: All strategies fire simultaneously with fixed weights (simpler, less adaptive)
• Recommendation: Keep enabled for all markets; system needs 2-3 months to mature
Learning Rate (0.01-0.20):
• Function: Speed of parameter adaptation based on outcomes
• Stocks/ETFs: 0.03-0.05 (slower, more stable)
• Crypto: 0.05-0.08 (faster, adapts to volatility)
• Forex: 0.04-0.06 (moderate)
• Timeframes:
1-5min scalping: 0.08-0.10 (rapid adaptation)
15min-1H day trading: 0.05-0.07 (balanced)
4H-Daily swing: 0.03-0.05 (conservative)
• Tradeoff: Higher = responsive but may overfit; Lower = stable but slower to adapt
Min Samples Per Regime (5-30):
• Function: Trades required before exiting bootstrap mode
• Active trading (>5 signals/day): 8-10 trades
• Moderate (1-5 signals/day): 10-15 trades
• Swing (few signals/week): 5-8 trades
• Logic: Bootstrap mode until this threshold; then uses Sharpe/Calmar for regime filtering
• Tradeoff: Lower = faster exit (risky, less data); Higher = more validation (safer, slower)
🌍 REGIME DETECTION:
Regime Lookback Period (20-200):
• Function: Bars used for linear regression to classify regime
• By Timeframe:
1-5min: 30-50 bars (~2-4 hour context)
15min: 40-60 bars (daily context)
1H: 50-100 bars (weekly context)
4H: 100-150 bars (monthly context)
Daily: 50-75 bars (quarterly context)
• By Market:
Crypto: 40-60 (faster regime changes)
Forex: 50-75 (moderate stability)
Stocks: 60-100 (slower structural trends)
• Tradeoff: Shorter = more regime switches (reactive); Longer = fewer switches (stable)
Trend Strength Threshold (0.1-0.8):
• Function: Minimum normalized LR slope to classify as trending vs ranging
• Lower (0.1-0.2): More markets classified as trending
• Higher (0.4-0.6): Only strong trends qualify
• Recommendations:
Choppy markets (BTC, small caps): 0.25-0.35
Smooth trends (major FX pairs): 0.30-0.40
Strong trends (indices during bull): 0.20-0.30
• Effect: Controls sensitivity of trending vs ranging classification
Vol Expansion Factor (1.2-3.0):
• Function: Volatility ratio to classify high-vol regimes (current_vol / avg_vol)
• By Asset:
Bitcoin: 1.4-1.6 (frequent vol spikes)
Altcoins: 1.3-1.5 (very volatile)
Major FX (EUR/USD): 1.6-2.0 (stable baseline)
Stocks (SPY): 1.5-1.8 (moderate)
Penny stocks: 1.3-1.4 (always volatile)
• Impact: Higher = fewer "High Vol Range" classifications; Lower = more sensitive to volatility spikes
🎯 SIGNAL GENERATION:
Base Quality Threshold (30-90):
• Function: Starting signal strength requirement (adapts per regime)
• THIS IS YOUR MAIN SIGNAL FREQUENCY CONTROL
• Conservative (70-80): Fewer, higher-quality signals
• Balanced (55-65): Moderate signal flow
• Aggressive (40-50): More signals, more noise
• By Trading Style:
Scalping (1-5min): 50-60
Day trading (15min-1H): 60-70
Swing (4H-Daily): 65-75
• Adaptive Behavior: System raises this in losing regimes (pickier), lowers in winning regimes (take more)
Min Confidence (0.1-0.9):
• Function: Minimum confidence score to fire signal
• Calculation: (Signal_Strength / 100) × Regime_Confidence
• Recommendations:
High-frequency (scalping): 0.2-0.3 (permissive)
Day trading: 0.3-0.4 (balanced)
Swing/position: 0.4-0.6 (selective)
• Interaction: During Transition regime (low regime confidence), even strong signals may fail confidence check; creates natural regime filtering
Only Trade Favorable Regimes (true/false):
• Function: Block signals in unfavorable regimes (where all strategies have negative risk-adjusted scores)
• Enabled (Recommended): Only trades when best strategy has positive Sharpe in current regime; auto-disables during bootstrap; protects capital
• Disabled: Always allows signals regardless of historical performance; use for manual regime assessment
• Bootstrap: Auto-allows trading until min_regime_samples reached, then switches to performance-based filtering
Min Bars Between Signals (1-20):
• Function: Prevents signal spam by enforcing minimum spacing
• By Timeframe:
1min: 3-5 bars (3-5 minutes)
5min: 3-6 bars (15-30 minutes)
15min: 4-8 bars (1-2 hours)
1H: 5-10 bars (5-10 hours)
4H: 3-6 bars (12-24 hours)
Daily: 2-5 bars (2-5 days)
• Logic: After signal fires, no new signals for X bars
• Tradeoff: Lower = more reactive (may overtrade); Higher = more patient (may miss reversals)
🌀 LORENTZIAN CORE:
Base Period (10-100):
• Function: Core time period for flow calculation (gets compressed by gamma)
• THIS IS YOUR PRIMARY TIMEFRAME KNOB
• By Timeframe:
1-5min scalping: 20-30 (fast response)
15min-1H day: 30-40 (balanced)
4H swing: 40-55 (smooth)
Daily position: 50-75 (very smooth)
• By Market Character:
Choppy (crypto, small caps): 25-35 (faster)
Smooth (major FX, indices): 35-50 (moderate)
Slow (bonds, utilities): 45-65 (slower)
• Gamma Effect: Actual length = base_period / gamma; High gamma compresses to ~20 bars, low gamma expands to ~50 bars
• Default 34 (Fibonacci) works well across most assets
Velocity Period (5-50):
• Function: Window for trend velocity calculation: (price_now - price ) / (N × ATR)
• By Timeframe:
1-5min scalping: 8-12 (fast momentum)
15min-1H day: 12-18 (balanced)
4H swing: 14-21 (smooth trend)
Daily: 18-30 (structural trend)
• By Market:
Crypto (fast moves): 10-14
Stocks (moderate): 14-20
Forex (smooth): 18-25
• Impact: Feeds into gamma calculation (v/c ratio); shorter = more sensitive to velocity spikes → higher gamma
• Relationship: Typically vel_period ≈ base_period / 2 to 2/3
Speed-of-Market (c) (0.5-3.0):
• Function: "Speed limit" for gamma calculation: c = realized_vol + vol_burst × c_multiplier
• By Asset Volatility:
High vol (BTC, TSLA): 1.0-1.3 (lower c = more compression)
Medium vol (SPY, EUR/USD): 1.3-1.6 (balanced)
Low vol (bonds, utilities): 1.6-2.5 (higher c = less compression)
• What It Does:
Lower c → velocity hits "speed limit" sooner → higher gamma → more compression
Higher c → velocity rarely hits limit → gamma stays near 1 → less adaptation
• Effect on Signals: More compression (low c) = faster regime detection, more responsive; Less compression (high c) = smoother, less adaptive
• Tuning: Start at 1.4; if gamma always ~1.0, lower to 1.0-1.2; if gamma spikes >5 often, raise to 1.6-2.0
Gamma Power (0.5-2.0):
• Function: Exponent applied to gamma: final_gamma = gamma^power
• Compression Strength:
0.5-0.8: Softens compression (gamma 4 → 2)
1.0: Linear (gamma 4 → 4)
1.2-2.0: Amplifies compression (gamma 4 → 16)
• Use Cases:
Reduce power (<1.0) if adaptive lengths swing too wildly or getting whipsawed
Increase power (>1.0) for more aggressive regime adaptation in fast markets
• Most users should leave at 1.0; only adjust if gamma behavior needs tuning
Max Kernel Lookback (20-200):
• Function: Computational limit for Lorentzian smoothing (performance control)
• Recommendations:
Fast PC / simple chart: 80-100
Slow PC / complex chart: 40-60
Mobile / lots of indicators: 30-50
• Impact: Each kernel smoothing loops through this many bars; higher = more accurate but slower
• Default 60 balances accuracy and speed; lower to 40-50 if indicator is slow
🎼 HARMONIC FLOW:
Short Horizon (0.2-1.0):
• Function: Fast timeframe multiplier: short_length = base_period × short_ratio / gamma
• Default: 0.5 (captures 2× faster flow than base)
• By Style:
Scalping: 0.3-0.4 (very fast)
Day trading: 0.4-0.6 (moderate)
Swing: 0.5-0.7 (balanced)
• Effect: Lower = more weight on micro-moves; Higher = smooths out fast fluctuations
Mid Horizon (0.5-2.0):
• Function: Medium timeframe multiplier: mid_length = base_period × mid_ratio / gamma
• Default: 1.0 (equals base_period, anchor timeframe)
• Usually keep at 1.0 unless specific strategy needs fine-tuning
Long Horizon (1.0-5.0):
• Function: Slow timeframe multiplier: long_length = base_period × long_ratio / gamma
• Default: 2.5 (captures trend/structure)
• By Style:
Scalping: 1.5-2.0 (less long-term influence)
Day trading: 2.0-3.0 (balanced)
Swing: 2.5-4.0 (strong trend component)
• Effect: Higher = more emphasis on larger structure; Lower = more reactive to recent price action
Short Weight (0-1):
Mid Weight (0-1):
Long Weight (0-1):
• Function: Relative importance in HFL calculation (should sum to 1.0)
• Defaults: Short: 0.45, Mid: 0.35, Long: 0.20 (day trading balanced)
• Preset Configurations:
SCALPING (fast response):
Short: 0.60, Mid: 0.30, Long: 0.10
DAY TRADING (balanced):
Short: 0.45, Mid: 0.35, Long: 0.20
SWING (trend-following):
Short: 0.25, Mid: 0.35, Long: 0.40
• Effect: More short weight = responsive but noisier; More long weight = smoother but laggier
🧠 DUAL MEMORY SYSTEM:
Enable Pattern Memory (true/false):
• Function: Master switch for KNN pattern matching via dual memory
• Enabled (Recommended): Strategy C (Memory Pattern) can fire; memory predictions influence all strategies; prediction arcs shown; heatmaps available
• Disabled: Only Strategy A and B available; faster performance (less computation); pure technical analysis (no pattern matching)
• Keep enabled for full system capabilities; disable only if CPU-constrained or testing pure flow signals
STM Size (50-200):
• Function: Short-Term Memory capacity (recent pattern storage)
• Characteristics: Fast decay (0.980), captures current regime, updates every 10 bars, tactical pattern matching
• Sizing:
Active markets (crypto): 80-120
Moderate (stocks): 100-150
Slow (bonds): 50-100
• By Timeframe:
1-15min: 60-100 (captures few hours of patterns)
1H: 80-120 (captures days)
4H-Daily: 100-150 (captures weeks/months)
• Tradeoff: More = better recent pattern coverage; Less = faster computation
• Default 100 is solid for most use cases
LTM Size (256-1024):
• Function: Long-Term Memory capacity (validated pattern storage)
• Characteristics: Slow decay (0.997), only high-quality patterns (gated), regime-specific recall, strategic pattern library
• Sizing:
Fast PC: 512-768
Medium PC: 384-512
Slow PC/Mobile: 256-384
• By Data Needs:
High-frequency (lots of patterns): 512-1024
Moderate activity: 384-512
Low-frequency (swing): 256-384
• Performance Impact: Each KNN search loops through entire LTM; 512 = good balance of coverage and speed; if slow, drop to 256-384
• Fills over weeks/months with validated patterns
STM Decay (0.95-0.995):
• Function: Short-Term Memory age decay rate: age_weight = decay^bars_since_pattern
• Decay Rates:
0.950: Aggressive fade (50% weight after 14 bars)
0.970: Moderate fade (50% after 23 bars)
0.980: Balanced (50% after 35 bars)
0.990: Slow fade (50% after 69 bars)
• By Timeframe:
1-5min: 0.95-0.97 (fast markets, old patterns irrelevant)
15min-1H: 0.97-0.98 (balanced)
4H-Daily: 0.98-0.99 (slower decay)
• Philosophy: STM should emphasize RECENT patterns; lower decay = only very recent matters; 0.980 works well for most cases
LTM Decay (0.99-0.999):
• Function: Long-Term Memory age decay rate
• Decay Rates:
0.990: 50% weight after 69 bars
0.995: 50% weight after 138 bars
0.997: 50% weight after 231 bars
0.999: 50% weight after 693 bars
• Philosophy: LTM should retain value for LONG periods; pattern from 6 months ago might still matter
• Usage:
Fast-changing markets: 0.990-0.995
Stable markets: 0.995-0.998
Structural patterns: 0.998-0.999
• Warning: Be careful with very high decay (>0.998); market structure changes, old patterns may mislead
• 0.997 balances long-term memory with regime evolution
K Neighbors (3-21):
• Function: Number of similar patterns to query in KNN search
• By Sample Size:
Small dataset (<100 patterns): 3-5
Medium dataset (100-300): 5-8
Large dataset (300-1000): 8-13
Very large (>1000): 13-21
• Tradeoff:
Fewer K (3-5): More reactive to closest matches; noisier; outlier-sensitive; better when patterns very distinct
More K (13-21): Smoother, more stable predictions; may dilute strong signals; better when patterns overlap
• Rule of Thumb: K ≈ √(memory_size) / 3; For STM=100, LTM=512: K ≈ 8-10 ideal
Adaptive Quality Gate (true/false):
• Function: Adapts LTM entry threshold per regime based on Sharpe ratio
• Enabled: Quality gate adapts: Low Sharpe → RAISE gate (demand better patterns); High Sharpe → LOWER gate (accept more patterns); each regime has independent gate
• Disabled: Fixed quality gate (0.4 default) for all regimes
• Recommended: Keep ENABLED; helps LTM focus on proven pattern types per regime; prevents weak patterns from polluting memory
🎯 MULTI-STRATEGY SYSTEM:
Enable Strategy Learning (true/false):
• Function: Core learning feature for regime-specific strategy selection
• Enabled: Tracks 3 strategies × 5 regimes = 15 performance matrices; selects best strategy per regime via Sharpe/Calmar/WinRate; adaptive strategy switching
• Disabled: All strategies fire simultaneously (weighted combination); no regime-specific selection; simpler but less adaptive
• Recommended: ENABLED (this is the core of the adaptive system); disable only for testing or simplification
Strategy A Weight (0-1):
• Function: Weight for Strategy A (Squeeze Breakout) when multi-strategy disabled
• Characteristics: Fires on Bollinger squeeze release; best in Low Vol Range, Transition; compression → expansion pattern
• When Multi-Strategy OFF: Default 0.33 (equal weight); increase to 0.4-0.5 for choppy ranges with breakouts; decrease to 0.2-0.3 for trending markets
• When Multi-Strategy ON: This is ignored (system auto-selects based on performance)
Strategy B Weight (0-1):
• Function: Weight for Strategy B (Lorentzian Flow) when multi-strategy disabled
• Characteristics: Fires on strong HFL + velocity + gamma; best in Trending Bull/Bear; momentum → acceleration pattern
• When Multi-Strategy OFF: Default 0.33; increase to 0.4-0.5 for trending markets; decrease to 0.2-0.3 for choppy/ranging markets
• When Multi-Strategy ON: Ignored (auto-selected)
Strategy C Weight (0-1):
• Function: Weight for Strategy C (Memory Pattern) when multi-strategy disabled
• Characteristics: Fires when dual KNN predicts strong move; best in High Vol Range; requires memory system enabled + sufficient data
• When Multi-Strategy OFF: Default 0.34; increase to 0.4-0.6 if strong pattern repetition and LTM has >200 patterns; decrease to 0.2-0.3 if new to system; set to 0.0 if memory disabled
• When Multi-Strategy ON: Ignored (auto-selected)
📚 PRE-TRAINING:
Historical Pre-Training (true/false):
• Function: Bootstrap feature that fills memory on chart load
• Enabled: Scans past bars to populate STM/LTM before live trading; calculates historical outcomes (10-bar forward returns); builds initial pattern library; system starts with context, not blank slate
• Disabled: Memories only populate in real-time; takes weeks to build pattern library
• Recommended: ENABLED (critical for avoiding "cold start" problem); disable only for testing clean learning
Training Bars (50-500):
• Function: How many historical bars to scan on load (limited by available history)
• Recommendations:
1-5min charts: 200-300 (few hours of history)
15min-1H: 200-400 (days/weeks)
4H: 300-500 (months)
Daily: 200-400 (years)
• Performance:
100 bars: ~1 second
300 bars: ~2-3 seconds
500 bars: ~4-5 seconds
• Sweet Spot: 200-300 (enough patterns without slow load)
• If chart loads slowly: Reduce to 100-150
🎨 VISUALIZATION:
Show Regime Background (true/false):
• Function: Color-code background by current regime
• Colors: Trending Bull (green tint), Trending Bear (red tint), High Vol Range (orange tint), Low Vol Range (blue tint), Transition (purple tint)
• Helps visually track regime changes
Show Flow Bands (true/false):
• Function: Plot upper/lower bands based on HFL strength
• Shows dynamic support/resistance zones; green fill = bullish flow; red fill = bearish flow
• Useful for visual trend confirmation
Show Confidence Meter (true/false):
• Function: Plot signal confidence (0-100) in separate pane
• Calculation: (Signal_Strength / 100) × Regime_Confidence
• Gold line = current confidence; dashed line = minimum threshold
• Signals fire when confidence exceeds threshold
Show Prediction Arc (true/false):
• Function: Dashed line projecting expected price move based on memory prediction
• NOT a price target - a probability vector; steep arc = strong expected move; flat arc = weak/uncertain prediction
• Green = bullish prediction; red = bearish prediction
Show Signals (true/false):
• Function: Triangle markers at entry points
• ▲ Green = Long signal; ▼ Red = Short signal
• Markers show on bar close (non-repainting)
🏆 DASHBOARD:
Show Dashboard (true/false):
• Function: Main info panel showing all system metrics
• Sections: Lorentzian Core, Regime, Dual Memory, Adaptive Parameters, Regime Performance, Shadow Portfolios, Current Signal Status
• Essential for understanding system state
Dashboard Position: Top Left, Top Right, Bottom Left, Bottom Right
Individual Section Toggles:
• System Stats: Lorentzian Core section (Gamma, v/c, HFL, TCI)
• Memory Stats: Dual Memory section (STM/LTM predictions, agreement)
• Shadow Portfolios: Shadow Portfolio table (equity, win%, PF)
• Adaptive Params: Adaptive Parameters section (threshold, quality gate, flow mult)
🔥 HEATMAPS:
Show Dual Heatmaps (true/false):
• Function: Visual pattern density maps for STM and LTM
• Layout: X-axis = pattern age (left=recent, right=old); Y-axis = outcome direction (top=bearish, bottom=bullish); Color intensity = pattern count; Color hue = bullish (green) vs bearish (red)
• Warning: Can clutter chart; disable if not using
Heatmap Position: Screen position for heatmaps (STM at selected position, LTM offset)
Resolution (5-15):
• Function: Grid resolution (bins)
• Higher = more detailed but smaller cells; Lower = clearer but less granular
• 10 is good balance; reduce to 6-8 if hard to read
PART 11: DASHBOARD METRICS EXPLAINED
The comprehensive dashboard provides real-time transparency into every aspect of the adaptive system:
⚡ LORENTZIAN CORE SECTION:
Gamma (γ):
• Range: 1.0 to ~10.0 (capped)
• Interpretation:
γ ≈ 1.0-1.2: Normal market time, low velocity
γ = 1.5-2.5: Moderate compression, trending
γ = 3.0-5.0: High compression, explosive moves
γ > 5.0: Extreme compression, parabolic volatility
• Usage: High gamma = system operating in compressed time; expect shorter effective periods and faster adaptation
v/c (Velocity / Speed Limit):
• Range: 0.0 to 0.999 (approaches but never reaches 1.0)
• Interpretation:
v/c < 0.3: Slow market, low momentum
v/c = 0.4-0.7: Moderate trending
v/c > 0.7: Approaching "speed limit," high velocity
v/c > 0.9: Parabolic move, system at limit
• Color Coding: Red (>0.7), Gold (0.4-0.7), Green (<0.4)
• Usage: High v/c warns of extreme conditions where trend may exhaust
HFL (Harmonic Flow):
• Range: Typically -3.0 to +3.0 (can exceed in extremes)
• Interpretation:
HFL > 0: Bullish flow
HFL < 0: Bearish flow
|HFL| > 0.5: Strong directional bias
|HFL| < 0.2: Weak, indecisive
• Color: Green (positive), Red (negative)
• Usage: Primary directional indicator; strategies often require HFL confirmation
TCI (Temporal Compression Index):
• Calculation: base_period / compressed_length
• Interpretation:
TCI ≈ 1.0: No compression, normal time
TCI = 1.5-2.5: Moderate compression
TCI > 3.0: Significant compression
• Usage: Shows how much time is being compressed; mirrors gamma but more intuitive
╔═══ REGIME SECTION ═══╗
Current:
• Display: Regime name with icon (Trending Bull ↗, Trending Bear ↘, High Vol Range ↔, Low Vol Range —, Transition ⚡)
• Color: Gold for visibility
• Usage: Know which regime you're in; check regime performance to see expected strategy behavior
Confidence:
• Range: 0-100%
• Interpretation:
>70%: Very clear regime definition
40-70%: Moderate clarity
<40%: Ambiguous, mixed conditions
• Color: Green (>70%), Gold (40-70%), Red (<40%)
• Usage: High confidence = trust regime classification; low confidence = regime may be transitioning
Mode:
• States:
🔥 BOOTSTRAP (X/10): Still gathering data for this regime
✅ FAVORABLE: Best strategy has positive risk-adjusted score (>0.5)
⚠️ UNFAVORABLE: All strategies have negative scores (≤0.5)
• Color: Orange (bootstrap), Green (favorable), Red (unfavorable)
• Critical Importance: This tells you whether the system will trade or stand aside (if regime filter enabled)
╔═══ DUAL MEMORY KNN SECTION ═══╗
STM (Size):
• Display: Number of patterns currently in STM (0 to stm_size)
• Interpretation: Should fill to capacity within hours/days; if not filling, check that memory is enabled
STM Pred:
• Range: Typically -0.05 to +0.05 (representing -5% to +5% expected 10-bar move)
• Color: Green (positive), Red (negative)
• Usage: STM's prediction based on recent patterns; emphasis on current regime
LTM (Size):
• Display: Number of patterns in LTM (0 to ltm_size)
• Interpretation: Fills slowly (weeks/months); only validated high-quality patterns; check quality gate if not filling
LTM Pred:
• Range: Similar to STM pred
• Color: Green (positive), Red (negative)
• Usage: LTM's prediction based on long-term validated patterns; more strategic than tactical
Agreement:
• Display:
✅ XX%: Strong agreement (>70%) - both memories aligned
⚠️ XX%: Moderate agreement (40-70%) - some disagreement
❌ XX%: Conflict (<40%) - memories strongly disagree
• Color: Green (>70%), Gold (40-70%), Red (<40%)
• Critical Usage: Low agreement often precedes regime change or signals novel conditions; Strategy C won't fire with low agreement
╔═══ ADAPTIVE PARAMS SECTION ═══╗
Threshold:
• Display: Current regime's signal quality threshold (30-90)
• Interpretation: Higher = pickier; lower = more permissive
• Watch For: If steadily rising in a regime, system is struggling (low win rate); if falling, system is confident
• Default: Starts at base_quality_threshold (usually 60)
Quality:
• Display: Current regime's LTM quality gate (0.2-0.8)
• Interpretation: Minimum quality score for pattern to enter LTM
• Watch For: If rising, system demanding higher-quality patterns; if falling, accepting more diverse patterns
• Default: Starts at 0.4
Flow Mult:
• Display: Current regime's flow multiplier (0.5-2.0)
• Interpretation: Amplifies or dampens HFL for Strategy B
• Watch For: If >1.2, system found strong edge in flow signals; if <0.8, flow signals underperforming
• Default: Starts at 1.0
Learning:
• Display: ✅ ON or ❌ OFF
• Shows whether adaptive learning is enabled
• Color: Green (on), Red (off)
╔═══ REGIME PERFORMANCE SECTION ═══╗
This table shows ONLY the current regime's statistics:
S (Strategy):
• Display: A, B, or C
• Color: Gold if selected strategy; gray if not
• Shows which strategies have data in this regime
Trades:
• Display: Number of completed trades for this pair
• Interpretation: Blank or low numbers mean bootstrap mode; >10 means statistical significance building
Win%:
• Display: Win rate percentage
• Color: Green (>55%), White (45-55%), Red (<45%)
• Interpretation: 52%+ is good; 58%+ is excellent; <45% means struggling
• Note: Short-term variance is normal; judge after 20+ trades
Sharpe:
• Display: Annualized Sharpe ratio
• Color: Green (>1.0), White (0-1.0), Red (<0)
• Interpretation:
>2.0: Exceptional (rare)
1.0-2.0: Good
0.5-1.0: Acceptable
0-0.5: Marginal
<0: Losing
• Usage: Primary metric for strategy selection (60% weight in score)
╔═══ SHADOW PORTFOLIOS SECTION ═══╗
Shows virtual equity tracking across ALL regimes (not just current):
S (Strategy):
• Display: A, B, or C
• Color: Gold if currently selected strategy; gray otherwise
Equity:
• Display: Current virtual balance (starts $10,000)
• Color: Green (>$10,000), White ($9,500-$10,000), Red (<$9,500)
• Interpretation: Which strategy is actually making virtual money across all conditions
• Note: 10% risk per trade assumed
Win%:
• Display: Overall win rate across all regimes
• Color: Green (>55%), White (45-55%), Red (<45%)
• Interpretation: Aggregate performance; strategy may do well in some regimes and poorly in others
PF (Profit Factor):
• Display: Gross profit / gross loss
• Color: Green (>1.5), White (1.0-1.5), Red (<1.0)
• Interpretation:
>2.0: Excellent
1.5-2.0: Good
1.2-1.5: Acceptable
1.0-1.2: Marginal
<1.0: Losing
• Usage: Confirms win rate; high PF with moderate win rate means winners >> losers
╔═══ STATUS BAR ═══╗
Display States:
• 🟢 LONG: Currently in long position (green background)
• 🔴 SHORT: Currently in short position (red background)
• ⬆️ LONG SIGNAL: Long signal present but not yet confirmed (waiting for bar close)
• ⬇️ SHORT SIGNAL: Short signal present but not yet confirmed
• ⚪ NEUTRAL: No position, no signal (white background)
Usage: Immediate visual confirmation of system state; check before manually entering/exiting
PART 12: VISUAL ELEMENT INTERPRETATION
REGIME BACKGROUND COLORS:
Green Tint: Trending Bull regime - expect Strategy B (Flow) to dominate; focus on long momentum
Red Tint: Trending Bear regime - expect Strategy B (Flow) shorts; focus on short momentum
Orange Tint: High Vol Range - expect Strategy A (Squeeze) or C (Memory); trade breakouts or patterns
Blue Tint: Low Vol Range - expect Strategy A (Squeeze); wait for compression release
Purple Tint: Transition regime - often unfavorable; system may stand aside; high uncertainty
Usage: Quick visual regime identification without reading dashboard
FLOW BANDS:
Upper Band: close + HFL × ATR × 1.5
Lower Band: close - HFL × ATR × 1.5
Green Fill: HFL positive (bullish flow); bands act as dynamic support/resistance in uptrend
Red Fill: HFL negative (bearish flow); bands act as dynamic resistance/support in downtrend
Usage:
• Bullish flow: Price bouncing off lower band = trend continuation; breaking below = possible reversal
• Bearish flow: Price rejecting upper band = trend continuation; breaking above = possible reversal
CONFIDENCE METER (Separate Pane):
Gold Line: Current signal confidence (0-100)
Dashed Line: Minimum confidence threshold
Interpretation:
• Line above threshold: Signal likely to fire if strength sufficient
• Line below threshold: Even if signal logic met, won't fire (insufficient confidence)
• Gradual rise: Signal building strength
• Sharp spike: Sudden conviction (check if sustainable)
Usage: Real-time signal probability; helps anticipate upcoming entries
PREDICTION ARC:
Dashed Line: Projects from current close to expected price 8 bars forward
Green Arc: Bullish memory prediction
Red Arc: Bearish memory prediction
Steep Arc: High conviction (strong expected move)
Flat Arc: Low conviction (weak/uncertain move)
Important: NOT a price target; this is a probability vector based on KNN outcomes; actual price may differ
Usage: Directional bias from pattern matching; confirms or contradicts flow signals
SIGNAL MARKERS:
▲ Green Triangle (below bar):
• Long signal confirmed on bar close
• Entry on next bar open
• Non-repainting (appears after bar closes)
▼ Red Triangle (above bar):
• Short signal confirmed on bar close
• Entry on next bar open
• Non-repainting
Size: Tiny (unobtrusive)
Text: "L" or "S" in marker
Usage: Historical signal record; alerts should fire on these; verify against dashboard status
DUAL HEATMAPS (If Enabled):
STM HEATMAP:
• X-axis: Pattern age (left = recent, right = older, typically 0-50 bars)
• Y-axis: Outcome direction (top = bearish outcomes, bottom = bullish outcomes)
• Color Intensity: Brightness = pattern count in that cell
• Color Hue: Green tint (bullish), Red tint (bearish), Gray (neutral)
Interpretation:
• Dense bottom-left: Many recent bullish patterns (bullish regime)
• Dense top-left: Many recent bearish patterns (bearish regime)
• Scattered: Mixed outcomes, ranging regime
• Empty areas: Few patterns (low data)
LTM HEATMAP:
• Similar layout but X-axis spans wider age range (0-500+ bars)
• Shows long-term pattern distribution
• Denser = more validated patterns
Comparison Usage:
• If STM and LTM heatmaps look similar: Current regime matches historical patterns (high agreement)
• If STM bottom-heavy but LTM top-heavy: Recent bullish activity contradicts historical bearish patterns (low agreement, transition signal)
PART 13: DEVELOPMENT STORY
The creation of the Lorentzian Harmonic Flow Adaptive ML system represents over six months of intensive research, mathematical exploration, and iterative refinement. What began as a theoretical investigation into applying special relativity to market time evolved into a complete adaptive learning framework.
THE CHALLENGE:
The fundamental problem was this: markets don't experience time uniformly, yet every indicator treats a 50-period calculation the same whether markets are exploding or sleeping. Traditional adaptive indicators adjust parameters based on volatility, but this is reactive—by the time you measure high volatility, the explosive move is over. What was needed was a framework that measured the market's intrinsic velocity relative to its own structural limits, then compressed time itself proportionally.
THE LORENTZIAN INSIGHT:
Einstein's special relativity provides exactly this framework through the Lorentz factor. When an object approaches the speed of light, time dilates—but from the object's reference frame, it experiences time compression. By treating price velocity as analogous to relativistic velocity and volatility structure as the "speed limit," we could calculate a gamma factor that compressed lookback periods during explosive moves.
The mathematics were straightforward in theory but devilishly complex in implementation. Pine Script has no native support for dynamically-sized arrays or recursive functions, forcing creative workarounds. The Lorentzian kernel smoothing required nested loops through historical bars, calculating kernel weights on the fly—a computational nightmare. Early versions crashed or produced bizarre artifacts (negative gamma values, infinite loops during volatility spikes).
Optimization took weeks. Limiting kernel lookback to 60 bars while still maintaining smoothing quality. Pre-calculating gamma once per bar and reusing it across all calculations. Caching intermediate results. The final implementation balances mathematical purity with computational reality.
THE MEMORY ARCHITECTURE:
With temporal compression working, the next challenge was pattern memory. Simple moving average systems have no memory—they forget yesterday's patterns immediately. But markets are non-stationary; what worked last month may not work today. The solution: dual-memory architecture inspired by cognitive neuroscience.
Short-Term Memory (STM) would capture tactical patterns—the hippocampus of the system. Fast encoding, fast decay, always current. Long-Term Memory (LTM) would store validated strategic patterns—the neocortex. Slow consolidation, persistent storage, regime-spanning wisdom.
The KNN implementation nearly broke me. Calculating Lorentzian distance across 6 dimensions for 500+ patterns per query, applying age decay, filtering by regime, finding K nearest neighbors without native sorting functions—all while maintaining sub-second execution. The breakthrough came from realizing we could use destructive sorting (marking found neighbors as "infinite distance") rather than maintaining separate data structures.
Pre-training was another beast. To populate memory with historical patterns, the system needed to scan hundreds of past bars, calculate forward outcomes, and insert patterns—all on chart load without timing out. The solution: cap at 200 bars, optimize loops, pre-calculate features. Now it works seamlessly.
THE REGIME DETECTION:
Five-regime classification emerged from empirical observation. Traditional trending/ranging dichotomy missed too much nuance. Markets have at least four distinct states: trending up, trending down, volatile range, quiet range—plus a chaotic transition state. Linear regression slope quantifies trend; volatility ratio quantifies expansion; combining them creates five natural clusters.
But classification is useless without regime-specific learning. That meant tracking 15 separate performance matrices (3 strategies × 5 regimes), computing Sharpe ratios and Calmar ratios for sparse data, implementing Bayesian-like strategy selection. The bootstrap mode logic alone took dozens of iterations—too strict and you never get data, too permissive and you blow up accounts during learning.
THE ADAPTIVE LAYER:
Parameter adaptation was conceptually elegant but practically treacherous. Each regime needed independent thresholds, quality gates, and multipliers that adapted based on outcomes. But naive gradient descent caused oscillations—win a few trades, lower threshold, take worse signals, lose trades, raise threshold, miss good signals. The solution: exponential smoothing via learning rate (α) and separate scoring for selection vs adaptation.
Shadow portfolios provided objective validation. By running virtual accounts for all strategies simultaneously, we could see which would have won even when not selected. This caught numerous bugs where selection logic was sound but execution was flawed, or vice versa.
THE DASHBOARD & VISUALIZATION:
A learning system is useless if users can't understand what it's doing. The dashboard went through five complete redesigns. Early versions were information dumps—too much data, no hierarchy, impossible to scan. The final version uses visual hierarchy (section headers, color coding, strategic whitespace) and progressive disclosure (show current regime first, then performance, then parameters).
The dual heatmaps were a late addition but proved invaluable for pattern visualization. Seeing STM cluster in one corner while LTM distributed broadly immediately signals regime novelty. Traders grasp this visually faster than reading disagreement percentages.
THE TESTING GAUNTLET:
Testing adaptive systems is uniquely challenging. Static backtest results mean nothing—the system should improve over time. Early "tests" showed abysmal performance because bootstrap periods were included. The breakthrough: measure pre-learning baseline vs post-learning performance. A system going from 48% win rate (first 50 trades) to 56% win rate (trades 100-200) is succeeding even if absolute performance seems modest.
Edge cases broke everything repeatedly. What happens when a regime never appears in historical data? When all strategies fail simultaneously? When memory fills with only bearish patterns during a bull run? Each required careful handling—bootstrap modes, forced diversification, quality gates.
THE DOCUMENTATION:
This isn't an indicator you throw on a chart with default settings and trade immediately. It's a learning system that requires understanding. The input tooltips alone contain over 10,000 words of guidance—market-specific recommendations, timeframe-specific settings, tradeoff explanations. Every parameter needed not just a description but a philosophical justification and practical tuning guide.
The code comments span 500+ lines explaining theory, implementation decisions, edge cases. Future maintainers (including myself in six months) need to understand not just what the code does but why certain approaches were chosen over alternatives.
WHAT ALMOST DIDN'T WORK:
The entire project nearly collapsed twice. First, when initial Lorentzian smoothing produced complete noise—hours of debugging revealed a simple indexing error where I was accessing instead of in the kernel loop. One character, entire system broken.
Second, when memory predictions showed zero correlation with outcomes. Turned out the KNN distance metric was dominated by the gamma dimension (values 1-10) drowning out normalized features (values -1 to 1). Solution: apply kernel transformation to all dimensions, not just final distance. Obvious in retrospect, maddening at the time.
THE PHILOSOPHY:
This system embodies a specific philosophy: markets are learnable but non-stationary. No single strategy works forever, but regime-specific patterns persist. Time isn't uniform, memory isn't perfect, prediction isn't possible—but probabilistic edges exist for those willing to track them rigorously.
It rejects the premise that indicators should give universal advice. Instead, it says: "In this regime, based on similar past states, Strategy B has a 58% win rate and 1.4 Sharpe. Strategy A has 45% and 0.2 Sharpe. I recommend B. But we're still in bootstrap for Strategy C, so I'm gathering data. Check back in 5 trades."
That humility—knowing what it knows and what it doesn't—is what makes it robust.
PART 14: PROFESSIONAL USAGE PROTOCOL
PHASE 1: DEPLOYMENT (Week 1-4)
Initial Setup:
1. Load indicator on primary trading chart with default settings
2. Verify historical pre-training enabled (should see ~200 patterns in STM/LTM on first load)
3. Enable all dashboard sections for maximum transparency
4. Set alerts but DO NOT trade real money
Observation Checklist:
• Dashboard Validation:
✓ Lorentzian Core shows reasonable gamma (1-5 range, not stuck at 1.0 or spiking to 10)
✓ HFL oscillates with price action (not flat or random)
✓ Regime classifications make intuitive sense
✓ Confidence scores vary appropriately
• Memory System:
✓ STM fills within first few hours/days of real-time bars
✓ LTM grows gradually (few patterns per day, quality-gated)
✓ Predictions show directional bias (not always 0.0)
✓ Agreement metric fluctuates with regime changes
• Bootstrap Tracking:
✓ Dashboard shows "🔥 BOOTSTRAP (X/10)" for each regime
✓ Trade counts increment on regime-specific signals
✓ Different regimes reach threshold at different rates
Paper Trading:
• Take EVERY signal (ignore unfavorable warnings during bootstrap)
• Log each trade: entry price, regime, selected strategy, outcome
• Calculate your actual P&L assuming proper risk management (1-2% risk per trade)
• Do NOT judge system performance yet—focus on understanding behavior
Troubleshooting:
• No signals for days:
- Check base_quality_threshold (try lowering to 50-55)
- Verify enable_regime_filter not blocking all regimes
- Confirm signal confidence threshold not too high (try 0.25)
• Signals every bar:
- Raise base_quality_threshold to 65-70
- Increase min_bars_between to 8-10
- Check if gamma spiking excessively (raise c_multiplier)
• Memory not filling:
- Confirm enable_memory = true
- Verify historical pre-training completed (check STM size after load)
- May need to wait 10 bars for first real-time update
PHASE 2: VALIDATION (Week 5-12)
Statistical Emergence:
By week 5-8, most regimes should exit bootstrap. Look for:
✓ Regime Performance Clarity:
- At least 2-3 strategies showing positive Sharpe in their favored regimes
- Clear separation (Strategy B strong in Trending, Strategy A strong in Low Vol Range, etc.)
- Win rates stabilizing around 50-60% for winning strategies
✓ Shadow Portfolio Divergence:
- Virtual portfolios showing clear winners ($10K → $11K+) and losers ($10K → $9K-)
- Profit factors >1.3 for top strategy
- System selection aligning with best shadow portfolio
✓ Parameter Adaptation:
- Thresholds varying per regime (not stuck at initial values)
- Quality gates adapting (some regimes higher, some lower)
- Flow multipliers showing regime-specific optimization
Validation Questions:
1. Do patterns make intuitive sense?
- Strategy B (Flow) dominating Trending Bull/Bear? ✓ Expected
- Strategy A (Squeeze) succeeding in Low Vol Range? ✓ Expected
- Strategy C (Memory) working in High Vol Range? ✓ Expected
- Random strategy winning everywhere? ✗ Problem
2. Is unfavorable filtering working?
- Regimes with negative Sharpe showing "⚠️ UNFAVORABLE"? ✓ System protecting capital
- Transition regime often unfavorable? ✓ Expected
- All regimes perpetually unfavorable? ✗ Settings too strict or asset unsuitable
3. Are memories agreeing appropriately?
- High agreement during stable regimes? ✓ Expected
- Low agreement during transitions? ✓ Expected (novel conditions)
- Perpetual conflict? ✗ Check memory sizes or decay rates
Fine-Tuning (If Needed):
Too Many Signals in Losing Regimes:
→ Increase learning_rate to 0.07-0.08 (faster adaptation)
→ Raise base_quality_threshold by 5-10 points
→ Enable regime filter if disabled
Missing Profitable Setups:
→ Lower base_quality_threshold by 5-10 points
→ Reduce min_confidence to 0.25-0.30
→ Check if bootstrap mode blocking trades (let it complete)
Excessive Parameter Swings:
→ Reduce learning_rate to 0.03-0.04
→ Increase min_regime_samples to 15-20 (more data before adaptation)
Memory Disagreement Too Frequent:
→ Increase LTM size to 768-1024 (broader pattern library)
→ Lower adaptive_quality_gate requirement (allow more patterns)
→ Increase K neighbors to 10-12 (smoother predictions)
PHASE 3: LIVE TRADING (Month 4+)
Pre-Launch Checklist:
1. ✓ At least 3 regimes show positive Sharpe (>0.8)
2. ✓ Top shadow portfolio shows >53% win rate and >1.3 profit factor
3. ✓ Parameters have stabilized (not changing more than 10% per month)
4. ✓ You understand every dashboard metric and can explain regime/strategy behavior
5. ✓ You have proper risk management plan independent of this system
Position Sizing:
Conservative (Recommended for Month 4-6):
• Risk per trade: 0.5-1.0% of account
• Max concurrent positions: 1-2
• Total exposure: 10-25% of intended full size
Moderate (Month 7-12):
• Risk per trade: 1.0-1.5% of account
• Max concurrent positions: 2-3
• Total exposure: 25-50% of intended size
Full Scale (Year 2+):
• Risk per trade: 1.5-2.0% of account
• Max concurrent positions: 3-5
• Total exposure: 100% (still following risk limits)
Entry Execution:
On Signal Confirmation:
1. Verify dashboard shows signal type (▲ LONG or ▼ SHORT)
2. Check regime mode (avoid if "⚠️ UNFAVORABLE" unless testing)
3. Note selected strategy (A/B/C) and its regime Sharpe
4. Verify memory agreement if Strategy C selected (want >60%)
Entry Method:
• Market entry: Next bar open after signal (for exact backtest replication)
• Limit entry: Slight improvement (2-3 ticks) if confident in direction
Stop Loss Placement:
• Strategy A (Squeeze): Beyond opposite band or recent swing point
• Strategy B (Flow): 1.5-2.0 ATR from entry against direction
• Strategy C (Memory): Based on predicted move magnitude (tighter if pred > 2%)
Exit Management:
System Exit Signals:
• Opposite signal fires: Immediate exit, potential reversal entry
• 20 bars no exit signal: System implies position stale, consider exiting
• Regime changes to unfavorable: Tighten stop, consider partial exit
Manual Exit Conditions:
• Stop loss hit: Take loss, log for validation (system expects some losses)
• Profit target hit: If using fixed targets (2-3R typical)
• Major news event: Flatten during high-impact news (system can't predict these)
Warning Signs (Exit Criteria):
🚨 Stop Trading If:
1. All regimes show negative Sharpe for 4+ weeks (market structure changed)
2. Your results >20% worse than shadow portfolios (execution problem)
3. Parameters hitting extremes (thresholds >85 or <35 across all regimes)
4. Memory agreement <30% for extended periods (unprecedented conditions)
5. Account drawdown >20% (risk management failure, system or otherwise)
⚠️ Reduce Size If:
1. Win rate drops 10%+ from peak (temporary regime shift)
2. Selected strategy underperforming another by >30% (selection lag)
3. Consecutive losses >5 (variance or problem, reduce until clarity)
4. Major market regime change (Fed policy shift, war, etc. - let system re-adapt)
PART 15: THEORETICAL IMPLICATIONS & LIMITATIONS
WHAT THIS SYSTEM REPRESENTS:
Contextual Bandits:
The regime-specific strategy selection implements a contextual multi-armed bandit problem. Each strategy is an "arm," each regime is a "context," and we select arms to maximize expected reward given context. This is reinforcement learning applied to trading.
Experience Replay:
The dual-memory architecture mirrors DeepMind's DQN breakthrough. STM = recent experience buffer; LTM = validated experience replay. This prevents catastrophic forgetting while enabling rapid adaptation—a key challenge in neural network training.
Meta-Learning:
The system learns how to learn. Parameter adaptation adjusts the system's own sensitivity and selectivity based on outcomes. This is "learning to learn"—optimizing the optimization process itself.
Non-Stationary Optimization:
Traditional backtesting assumes stationarity (past patterns persist). This system assumes non-stationarity and continuously adapts. The goal isn't finding "the best parameters" but tracking the moving optimum.
Regime-Conditional Policies:
Rather than a single strategy for all conditions, this implements regime-specific policies. This is contextual decision-making—environment state determines action selection.
FINAL WISDOM:
"The market is a complex adaptive system. To trade it successfully, one must also adapt. This indicator provides the framework—memory, learning, regime awareness—but wisdom comes from understanding when to trade, when to stand aside, and when to defer to conditions the system hasn't yet learned. The edge isn't in the algorithm alone; it's in the partnership between mathematical rigor and human judgment."
— Inspired by the intersection of Einstein's relativity, Kahneman's behavioral economics, and decades of quantitative trading research
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
COT Index by Luis TrompeterThe COT Index transforms the weekly COT net positions of Commercial traders into a normalized mathematical model.
Instead of displaying raw net positioning, the COT Index processes the data through a cyclical normalization algorithm (commonly using a 26-week or alternatively a 52-week cycle).
This makes it easier to identify bullish or bearish extremes in Commercial activity.
The index is plotted as a color-coded line:
• Green Zone – Commercials are mathematically classified as bullish.
Historically, bullish Commercial positioning often aligns with upward market pressure.
• Red Zone – Commercials are mathematically classified as bearish.
This typically corresponds with increased downward pressure in the underlying market.
• Neutral Zone – Neither bull nor bear dominance; positioning is mid-range.
Since COT data is published only once per week and the COT Index is built on cyclical multi-week analysis, the indicator is intended to be used exclusively on the weekly timeframe.
Using lower timeframes will not reflect the structure of the data accurately.
The selected cycle length (typically 26 weeks, optionally 52 weeks) determines how net positions are compared and normalized, and can influence how quickly extreme zones appear.
The COT Index provides an objective way to interpret Commercial trader sentiment and to identify potential directional bias in the market.
EMA & MA Alert Strategies8 Trading Strategies for Alerts:
Strategy 1: EMA Golden Cross / Death Cross
EMA1 crosses above EMA2 → bullish momentum
EMA1 crosses below EMA2 → bearish momentum
Stronger: EMA1 crosses EMA3
Strategy 2: MA Golden Cross / Death Cross
MA1 crosses above MA2 → trend reversal up
MA1 crosses below MA2 → trend reversal down
Strategy 3: EMA Alignment (Trend Direction)
Bullish: EMA1 > EMA2 > EMA3 (uptrend)
Bearish: EMA1 < EMA2 < EMA3 (downtrend)
Alerts when alignment changes
Strategy 4: Price vs EMA (Support/Resistance)
Price breaks above EMA2/EMA3 → bullish breakout
Price breaks below EMA2/EMA3 → bearish breakdown
Strategy 5: EMA vs MA Crossover
EMA1 crosses above MA1 → momentum exceeds trend
EMA2 crosses above MA2 → stronger momentum signal
Strategy 6: Pullback to EMA (Buy the Dip)
Price pulls back to EMA2/EMA3 and bounces → buy signal
Useful for entry during uptrends
Strategy 7: EMA Squeeze/Expansion
EMAs converging → potential breakout
EMAs expanding → trend acceleration
Strategy 8: Multi-Timeframe Confirmation
Price above all EMAs and MAs → strong uptrend
Price below all EMAs and MAs → strong downtrend
TradeBeard Larry Williams A/D + Classic DivergenceName: TradeBeard – Larry Williams A/D + Classic Divergence
What it does:
This indicator plots a classic Larry Williams Accumulation/Distribution (A/D) line, using:
(Close−Open)/(High−Low)×Volume
It then looks at price swings vs. A/D swings and marks true Larry-style divergences:
Bull Div – Price makes a lower low, but the A/D line makes a higher low → buying pressure/accumulation.
Bear Div – Price makes a higher high, but the A/D line makes a lower high → selling pressure/distribution.
Lines are drawn between the two pivots on the A/D line, with a label at the most recent pivot.
How to use / read it:
Use on any timeframe; the logic is the same.
Look for Bull Div near potential bottoms as confirmation that smart money is quietly buying.
Look for Bear Div near potential tops as confirmation that smart money is unloading.
Settings:
Pivot left bars (price) / Pivot right bars (price)
Controls how “wide” a swing high/low must be.
1 / 1 ≈ very sensitive (ICT/Larry-style 3-bar swings).
Higher values = fewer but cleaner swings and fewer signals.
Show bullish divergences / Show bearish divergences
Turn each signal type on or off.
Bullish color (line + label) / Bearish color (line + label)
Color of the divergence lines and label background.
Bullish label text color / Bearish label text color
Text color inside the Bull Div / Bear Div labels.
That’s it: pure Larry Williams A/D flow, price-based pivots, and clean visual divergence signals, wrapped in a TradeBeard skin.
I hope this will help you in your trading.
// Disclaimer:
// This script is for educational and informational purposes only.
// Trading and investing involve risk. You are fully responsible for your own decisions,
HTF EMA Ribbon Bias by HammerGeekThis indicator displays a higher-timeframe EMA-ribbon bias directly on any lower-timeframe chart. It uses four EMAs (5, 9, 13, 21) computed on the selected higher timeframe and detects the directional “stacking” of those EMAs to determine trend bias:
Bullish: EMAs are strictly stacked 5 > 9 > 13 > 21 (fully separated, no overlap)
Bearish: EMAs are strictly stacked 5 < 9 < 13 < 21
Neutral: Any overlap, crossing, or mixed order between the four EMAs
The indicator shades the background to show the bias: green for bullish, red for bearish, yellow for neutral. A built-in toggle lets you choose whether the bias should update live from the current higher-timeframe candle (faster, but may repaint) or only after the higher-timeframe candle closes (slower, but non-repainting).
Designed for traders who want clean, instantly readable higher-timeframe context—especially when working on lower-timeframe charts such as 30m, 15m, or 5m.
All settings can be modified to suit users' desires.
Advanced Market Profile & S/R Zones (Pro)Advanced Market Profile & S/R Zones
This indicator brings professional Auction Market Theory to your chart using a custom rolling Volume Profile algorithm. Unlike standard profiles that remain fixed, this tool dynamically calculates the "Fair Value" of the asset based on your specific lookback period (e.g., the last 100 bars).
It automatically highlights the Point of Control (POC), Value Area (VA), and suggests statistical Discount (Buy) and Premium (Sell) zones.
Key Features
Volume Splitting Algorithm:
Most basic scripts dump the entire volume of a candle into a single price point (the average). This script splits the volume across the candle's entire High-Low range. This results in a much smoother, higher-resolution bell curve that accurately reflects price action, especially on higher timeframes like Monthly charts.
Auto-generated Zones:
Green Zone (Discount): Prices below the Value Area Low (VAL). Statistically "cheap."
Red Zone (Premium): Prices above the Value Area High (VAH). Statistically "expensive."
Real-Time Dashboard:
A built-in panel displays the exact price levels for the POC, VAH, and VAL for precise limit order placement, along with the current Market Trend.
How to Use
For Intraday (Day Trading):
Settings: Set Lookback to 100 - 300.
Strategy: Watch for price to open outside the Value Area. If price breaks back inside the Value Area, target the POC (Red Line).
For Macro (Monthly/Weekly Charts):
Settings: Set Lookback to 12 (1 Year) or 60 (5 Years).
Strategy: Identify multi-year structural support. When a monthly candle enters the Green Discount Zone of a 5-year profile, it is often a high-probability institutional entry point.
Trend Logic
The Dashboard indicates trend based on price location relative to value:
Strong Bullish: Price is accepted ABOVE the Value Area.
Strong Bearish: Price is accepted BELOW the Value Area.
Neutral / In VA: Price is chopping inside the Value Area.
Disclaimer
This is a "Rolling Profile." It calculates the profile based on the current lookback window relative to the latest bar. As new bars form, the lookback window shifts, and the profile updates to reflect the new dataset.
