Oversold Screener · Webhook v3.3#Oversold Screener · Webhook v3.3
US Equities · 15-minute signals · AVWAP entries A–F · Optional CVD gate
## TL;DR
This indicator finds short-term, emotion-driven selloffs in large, liquid US stocks and pings your webhook with a compact alert (symbol + 15-minute close time).
It anchors an Event-AVWAP at the first qualified 15-minute bar after the selloff and proposes disciplined “right-side” entries (A–F) as price mean-reverts back through statistically defined bands. Optional macro fuses and CVD filters help avoid catching knives.
---
## What it does
1. Universe filter (off-chart): You run this on constituents of S&P 500 / Nasdaq-100 / Nasdaq Golden Dragon (or your curated list of healthy companies).
2. Signal (Step-2): On the 15-minute timeframe—including extended hours—the script flags an “oversold event” when:
• Depth: Today’s drawdown vs yesterday’s RTH reference (min of yesterday’s VWAP and Close) is large.
• Relative: The stock underperforms both its market benchmark (e.g., SPY/QQQ) and its sector ETF over the same 16/32×15m windows.
• Macro fuses: If any of the following exceed thresholds, the signal is suppressed: VIX spike, market 16/32×15m selloff, sector 16/32×15m selloff.
• RSI guard: 1-hour RSI is below a configurable level (default 30).
• Cooldown: De-dupes repeated events; you won’t be spammed by the same name intraday.
3. Execution geometry: At the event bar’s close the indicator anchors an AVWAP calculated natively in 15m space and draws ±1σ/±2σ/±3σ bands from a rolling variance of typical price.
4. Entry proposals: It labels A–F entries when price regains key bands after first probing the lower ones (see below). Optional 15m CVD confirmation can be required.
5. Alerts: When the event closes, TradingView raises a single alert with a tiny JSON payload so your downstream AI/service can do the news check and decide.
---
## Why this approach works
• Depth vs yesterday’s RTH reference targets “fresh” dislocations rather than slow trends.
• Relative filters ensure the stock fell much more than both the market and its sector, isolating idiosyncratic panic.
• AVWAP from the event bar approximates the market’s true average position after the shock; band reclaims are robust right-side confirmations.
• Optional CVD (delta volume) catches sell-side exhaustion and buy-side emergence without requiring a full order-book feed.
• Macro fuses (VIX / market / sector) avoid swimming against systemic stress.
---
## Inputs (key)
Bench ETF / Sector ETF
Choose your market (SPY or QQQ) and sector ETF (XLK/XLF/XLY… or KWEB/CQQQ for China tech ADRs).
Depth & relative settings (15-minute space)
• Depth vs prior-day RTH reference: percentage thresholds for 16 and 32 bars.
• Relative to market & sector: underperformance thresholds over 16 and 32 bars.
Macro circuit breakers
• VIX max change (e.g., +8%/+12% over the session)
• Market max 16/32×15m selloff (e.g., −1.5% / −2.5%)
• Sector max 16/32×15m selloff (e.g., −2.0% / −3.0%)
If any one exceeds the limit, the signal is suppressed.
Momentum guard
• RSI(1h) < 30 (configurable).
AVWAP band engine (15m native)
• Bands: ±1σ / ±2σ / ±3σ with EMA smoothing and optional σ cap.
• Settling bars after anchor (default 1–3) to reduce immediate whipsaws.
Entry toggles
• Enable/disable A, B, C, D, E, F individually.
• Optional CVD gate (on/off), lookback window and reversal thresholds.
Housekeeping
• Debounce per ticker and per entry type.
• Entry window length (default 1 week) and per-type cap (show top 3 per event).
• Webhook on/off.
---
## Entries (A–F)
These are right-side confirmations; each requires first touching the prerequisite lower band before reclaiming a higher one.
A Touch ≤ −2σ, then cross up through −1σ (classic exhaustion → relief).
B Touch ≤ −1σ, then reclaim AVWAP (crowd average changes hands).
C Break −1σ up, retest near −1σ within N bars, then bounce (retest confirmation).
D After compression (low ATR%), reclaim AVWAP (coiled spring).
E Touch ≤ −2σ, then reclaim AVWAP after a base (deeper flush → stronger reclaim).
F Touch ≤ −3σ, then cross up through −1σ (capitulation → violent mean reversion).
Optional CVD gate (15m): require sell-pressure exhaustion and a CVD turn-up before validating entries. Defaults are conservative so that A/F remain the highest-quality.
---
## Alert payload (minimal by design)
On event close, one alert is fired with a tiny JSON:
{
"event": "step2_signal",
"symbol": "TSLA",
"ts_15m_ms": 1730879700000
}
Use “Once per bar close” and the 15-minute chart. Your webhook receiver can enrich with fundamentals/news and decide Allow / Hold / Reject, then monitor A–F entries for execution.
---
## How to use
1. Run on your 15-minute chart with extended session enabled.
2. Create one alert per chart (or use TradingView’s multi-chart / watchlist alerts if you have Pro+).
3. Your backend ingests the minimal payload, fetches news and fundamentals, and returns a decision.
4. For Allowed names, watch the on-chart A–F labels; scale in across levels, scale out into upper HVNs/POC or AVWAP give-back.
---
## Defaults that work well
• RSI(1h) < 30
• Depth vs yesterday’s RTH ref: ≤ −4% (16 bars), ≤ −6% (32 bars)
• Relative to market/sector: ≤ −3% (16 bars), ≤ −4% (32 bars)
• Macro fuses: VIX day change ≤ +10%; market ≤ −2.0% / −3.0%; sector ≤ −2.5% / −3.5%
• AVWAP bands: EMA(σ)=3; σ cap off; settle ≥ 1 bar
• CVD gate off initially; enable after you’re comfortable with its behavior.
---
## Notes & limitations
• Indicator, not a strategy: it proposes event points and entries; position sizing and exits are up to you.
• Designed for US equities with ample liquidity; thin names will be noisy.
• Repainting: AVWAP and bands are anchored and do not repaint; entries are evaluated on bar close.
• To keep charts readable, we limit entry labels to the first three occurrences per type within the one-week window.
---
## What’s new in v3.3
• 15-minute event engine (always 15m, independent of the chart you view).
• Depth measured vs yesterday’s RTH VWAP/CLOSE (the lower of the two).
• Removed structure-health (SMA50 coverage) and MA50/200 position checks.
• Macro circuit breakers: VIX + market + sector thresholds; any one trips a fuse.
• RSI guard moved to 1-hour.
• AVWAP bands include ±3σ and new Entry F (−3σ → −1σ reclaim).
• Optional 15m CVD gate for entries.
• Minimal webhook payload for fast downstream AI checks.
• Debounce + entry-window caps to prevent over-labeling and to focus the week after the event.
• Numerous performance and stability tweaks in the 15m security sandbox.
---
## Disclaimer
This is a research tool. It does not constitute investment advice. Test in Replay first, start with small size, and respect your risk.
在脚本中搜索"GOLD"
hbd.mozanitstones - GoldThis PineScript indicator code aims to create an advanced composite trading system and generates buy/sell signals by combining multiple technical analyses. Essentially, the system utilizes a composite scoring mechanism using trend filters based on moving averages (EMA 50 and EMA 200) and various oscillators (such as RSI, MACD, and Stochastic) to support buy and sell decisions. It also integrates advanced confirmation tools such as the Multi-Timeframe (MTF) EMA filter, along with additional filters such as SuperTrend, Bollinger Bandwidth, and Volume Ratio. The code's key feature is that it generates final signals that meet both traditional signal conditions and the minimum number of confirmations achieved by weighting these various indicators, thus increasing signal reliability.
MTC – Multi-Timeframe Trend ConfirmatorMTC – Multi-Timeframe Trend Confirmator
The Ultimate Multi-Timeframe Trend Analysis Tool
MTC v6 is a comprehensive trend confirmation indicator that analyzes market conditions across multiple timeframes simultaneously. It combines six powerful technical indicators to give you a clear, visual representation of trend strength and direction.
🎯 Key Features
Visual Trend Gauge
Real-time trend strength display for 3 customizable timeframes
Progressive bar visualization (fills from left to right)
Color-coded signals: 🟢 Green (Bullish) | 🔴 Red (Bearish) | 🟡 Yellow (Ranging)
Score range: -10 to +10 for precise trend measurement
Multi-Indicator Analysis
The indicator combines 6 proven technical tools:
EMA 200 – Long-term trend direction
SMA 50/200 – Golden/Death cross signals
RSI 14 – Momentum confirmation
MACD – Trend strength validation
ADX (>25) – Trend intensity measurement (2x weight)
Supertrend – Dynamic support/resistance (2x weight)
⚙️ Customization Options
Flexible Timeframes: Set any timeframes you prefer (default: 15M, 1H, 4H)
Adjustable Gauge Size: Small, Medium, or Large display
Toggle Indicators: Enable/disable any of the 6 technical indicators
Supertrend Settings: Customize factor and ATR period
Built-in Alerts: Get notified when trends confirm
📈 How to Use
Score Interpretation:
Score > +2 = Bullish trend
Score < -2 = Bearish trend
Score between -2 and +2 = Ranging/Neutral
Multi-Timeframe Confirmation:
Look for alignment across timeframes for strongest signals
Higher timeframes confirm the overall trend direction
Lower timeframes help with precise entry timing
Visual Background:
Green background = Confirmed uptrend (Higher + Mid TF aligned)
Red background = Confirmed downtrend (Higher + Mid TF aligned)
💡 Perfect For
Swing traders seeking trend confirmation
Day traders analyzing multiple timeframes
Position traders validating long-term trends
Anyone who wants clear, visual trend analysis
Trade with confidence. Trade with confirmation. Trade with MTC
-Natantia
GutroThis TradingView indicator automatically plots Fibonacci retracement levels based on the day’s first confirmed swing between the session high and low (9:30 AM – 4 PM ET). It includes dynamic 0%, 38.2%, 50%, 61.8%, and 100% levels, a shaded golden zone, VWAP bands with standard-deviation envelopes, and a 9/21 EMA ribbon for trend confirmation.
Trend Entry_0 [TS_Indie]Trend Entry_0 — Mechanism Overview
The core structure of this strategy is based on a price action reversal pattern, as detailed below:
In the case of a Bullish Trend Reversal:
The price initially moves in a bearish direction. When candle A forms a low lower than the previous low, the high of candle A becomes a key reference point.
If the next candle closes above the high of candle A , it confirms a Bullish Trend Reversal.
* Upon a Bullish signal, a Long position is opened at the opening price of the next candle (candle B).
* When a subsequent Bearish signal occurs, the Long position is closed at the opening price of the next candle (candle C).
In the case of a Bearish Trend Reversal:
The price initially moves in a bullish direction. When candle A forms a high higher than the previous high, the low of candle A becomes a key reference point.
If the next candle closes below the low of candle A , it confirms a Bearish Trend Reversal.
* Upon a Bearish signal, a Short position is opened at the opening price of the next candle (candle B).
* When a subsequent Bullish signal occurs, the Short position is closed at the opening price of the next candle (candle C).
Options
* The start and end dates of the backtest can be customized.
* The swing lines of the trend can be displayed as an optional visual aid.
* The user can choose whether to open only Long or Short positions.
Backtest Results and Observations
Based on the backtesting results of this strategy across various assets and timeframes, it has been observed that this approach works best on trending assets such as Gold, BTC, and stocks.
It also performs well on higher timeframes, starting from the Daily timeframe and above, especially when taking Long positions only.
However, when applied to currency pairs such as EUR/USD, the results tend to be less impressive.
I encourage everyone to try backtesting and further developing this strategy — adding new conditions or filters may potentially lead to improved performance.
Disclaimer
This script is intended solely for backtesting purposes, based on a particular price action pattern.
It does not constitute financial or investment advice.
Backtest results do not guarantee future performance.
Relative Strength vs XAUIts a simple relative strength chart, right now i have set it with Gold, as it is outperforming most of indices globally.
Custom Checklist# Custom Checklist - Trading Preparation & Reminders
A fully customizable checklist overlay indicator for TradingView that helps traders maintain discipline and follow their trading routine systematically.
## 🎯 Purpose
This indicator serves as a visual reminder system on your charts to ensure you complete all necessary analysis steps before entering a trade. Perfect for traders who want to maintain consistency and avoid emotional or rushed trading decisions.
## ✨ Key Features
- **20 Customizable Lines**: Create your own checklist items with any text you need
- **Flexible Display Options**:
- Show/hide title header
- Toggle entire checklist on/off
- Position anywhere on chart (9 positions available)
- Adjustable text size (tiny to huge)
- **Symbol Filtering**: Option to show checklist only on specific symbols (BTC/USD, GOLD, SPX500, USOIL)
- **Customizable Appearance**:
- Background color
- Text color
- Border color
- Transparency controls
- **Clean Interface**: Empty by default - add only the items you need
## 📋 Use Cases
- **Morning Routine**: Daily market preparation checklist
- **Trade Entry Rules**: Verify all setup conditions are met
- **Risk Management**: Confirm stop-loss, position size, and exit strategy
- **Multi-Timeframe Analysis**: Ensure you checked all required timeframes
- **Technical Analysis**: Track which indicators and patterns you've reviewed
- **News & Events**: Remember to check economic calendar and news
- **Personal Rules**: Your custom trading rules and reminders
## 🎨 Customization
Every aspect is customizable:
- All 20 lines can be edited to your needs
- Only non-empty lines are displayed
- Table position adjustable to any corner or middle position
- Color scheme fully customizable to match your chart theme
- Text size scalable for different screen sizes
## 💡 How to Use
1. Add indicator to your chart
2. Open Settings > Checklist Items
3. Fill in your checklist items (Line 1, Line 2, etc.)
4. Customize colors and position in Display Settings
5. Optional: Enable "Show Only on Specific Symbols" to show on select instruments
## 🔧 Display Settings
- **Checklist Title**: Custom header for your checklist
- **Show Title Header**: Toggle title display
- **Show Checklist**: Master on/off switch
- **Symbol Filter**: Restrict display to specific trading instruments
- **Position**: 9 placement options (corners and middle positions)
- **Text Size**: 5 size options (tiny, small, normal, large, huge)
- **Colors**: Background, text, and border fully customizable
## 📝 Example Checklist Ideas
**Swing Trading:**
- Support/Resistance levels identified
- Trend direction confirmed
- Volume analysis completed
- RSI/MACD signals checked
- Risk/Reward ratio calculated
**Day Trading:**
- Pre-market review done
- Key levels marked
- Economic calendar checked
- Trading plan written
- Position size calculated
**Technical Analysis:**
- Multiple timeframe alignment
- Chart patterns identified
- Moving averages reviewed
- Fibonacci levels drawn
- Volume profile analyzed
## ⚙️ Technical Details
- Pine Script v6
- Overlay indicator (displays on main chart)
- Lightweight - no complex calculations
- No repainting
- Works on all timeframes and instruments
## 🎓 Perfect For
- Beginner traders learning systematic analysis
- Experienced traders maintaining discipline
- Anyone who wants visual trading reminders
- Traders following multi-step strategies
- Those prone to FOMO or emotional trading
---
**Note**: This is a visual tool only. It does not generate trading signals or perform analysis. It serves as a reminder checklist to help you follow your own trading process consistently.
Custom Checklist# Custom Checklist - Trading Preparation & Reminders
A fully customizable checklist overlay indicator for TradingView that helps traders maintain discipline and follow their trading routine systematically.
## 🎯 Purpose
This indicator serves as a visual reminder system on your charts to ensure you complete all necessary analysis steps before entering a trade. Perfect for traders who want to maintain consistency and avoid emotional or rushed trading decisions.
## ✨ Key Features
- **20 Customizable Lines**: Create your own checklist items with any text you need
- **Flexible Display Options**:
- Show/hide title header
- Toggle entire checklist on/off
- Position anywhere on chart (9 positions available)
- Adjustable text size (tiny to huge)
- **Symbol Filtering**: Option to show checklist only on specific symbols (BTC/USD, GOLD, SPX500, USOIL)
- **Customizable Appearance**:
- Background color
- Text color
- Border color
- Transparency controls
- **Clean Interface**: Empty by default - add only the items you need
## 📋 Use Cases
- **Morning Routine**: Daily market preparation checklist
- **Trade Entry Rules**: Verify all setup conditions are met
- **Risk Management**: Confirm stop-loss, position size, and exit strategy
- **Multi-Timeframe Analysis**: Ensure you checked all required timeframes
- **Technical Analysis**: Track which indicators and patterns you've reviewed
- **News & Events**: Remember to check economic calendar and news
- **Personal Rules**: Your custom trading rules and reminders
## 🎨 Customization
Every aspect is customizable:
- All 20 lines can be edited to your needs
- Only non-empty lines are displayed
- Table position adjustable to any corner or middle position
- Color scheme fully customizable to match your chart theme
- Text size scalable for different screen sizes
## 💡 How to Use
1. Add indicator to your chart
2. Open Settings > Checklist Items
3. Fill in your checklist items (Line 1, Line 2, etc.)
4. Customize colors and position in Display Settings
5. Optional: Enable "Show Only on Specific Symbols" to show on select instruments
## 🔧 Display Settings
- **Checklist Title**: Custom header for your checklist
- **Show Title Header**: Toggle title display
- **Show Checklist**: Master on/off switch
- **Symbol Filter**: Restrict display to specific trading instruments
- **Position**: 9 placement options (corners and middle positions)
- **Text Size**: 5 size options (tiny, small, normal, large, huge)
- **Colors**: Background, text, and border fully customizable
## 📝 Example Checklist Ideas
**Swing Trading:**
- Support/Resistance levels identified
- Trend direction confirmed
- Volume analysis completed
- RSI/MACD signals checked
- Risk/Reward ratio calculated
**Day Trading:**
- Pre-market review done
- Key levels marked
- Economic calendar checked
- Trading plan written
- Position size calculated
**Technical Analysis:**
- Multiple timeframe alignment
- Chart patterns identified
- Moving averages reviewed
- Fibonacci levels drawn
- Volume profile analyzed
## ⚙️ Technical Details
- Pine Script v6
- Overlay indicator (displays on main chart)
- Lightweight - no complex calculations
- No repainting
- Works on all timeframes and instruments
## 🎓 Perfect For
- Beginner traders learning systematic analysis
- Experienced traders maintaining discipline
- Anyone who wants visual trading reminders
- Traders following multi-step strategies
- Those prone to FOMO or emotional trading
---
**Note**: This is a visual tool only. It does not generate trading signals or perform analysis. It serves as a reminder checklist to help you follow your own trading process consistently.
Advanced Multi-Timeframe Moving AveragesThis indicator combines three fully customizable Moving Averages (MA30, MA80, MA120 by default) with multi-timeframe support, trend detection, and visual highlights — all in one lightweight script.
⚙️ Features
🕒 Multi-Timeframe Control – set a custom timeframe for each MA (e.g. MA30 from 1H, MA80 from 4H, MA120 from Daily).
🟢 Dynamic Trend Coloring – candles and background turn green when price is above all MAs, and red when below.
⚡ Crossover Alerts – built-in alerts for MA1↔MA2, MA2↔MA3, and MA1↔MA3 crossovers.
🎨 Optimized Colors – clear, bright MA colors for better visibility:
MA 1 (short-term): Gold (#FFD700)
MA 2 (mid-term): Deep Sky Blue (#00BFFF)
MA 3 (long-term): Hot Pink (#FF69B4)
🧩 Simple, Modular Design – easily adjust lengths, types (SMA/EMA), and timeframes from inputs.
🧠 How to Use
Add the indicator to your chart.
Set your preferred lengths (e.g. 30, 80, 120).
Optionally assign different timeframes for higher-TF analysis.
Use the color cues and crossovers to spot momentum shifts and trend changes.
🪶 Notes
Works great on all assets (crypto, forex, stocks, indices).
Compatible with both light and dark themes.
Built with Pine Script v5 — no external dependencies.
Scientific Correlation Testing FrameworkScientific Correlation Testing Framework - Comprehensive Guide
Introduction to Correlation Analysis
What is Correlation?
Correlation is a statistical measure that describes the degree to which two assets move in relation to each other. Think of it like measuring how closely two dancers move together on a dance floor.
Perfect Positive Correlation (+1.0): Both dancers move in perfect sync, same direction, same speed
Perfect Negative Correlation (-1.0): Both dancers move in perfect sync but in opposite directions
Zero Correlation (0): The dancers move completely independently of each other
In financial markets, correlation helps us understand relationships between different assets, which is crucial for:
Portfolio diversification
Risk management
Pairs trading strategies
Hedging positions
Market analysis
Why This Script is Special
This script goes beyond simple correlation calculations by providing:
Two different correlation methods (Pearson and Spearman)
Statistical significance testing to ensure results are meaningful
Rolling correlation analysis to track how relationships change over time
Visual representation for easy interpretation
Comprehensive statistics table with detailed metrics
Deep Dive into the Script's Components
1. Input Parameters Explained-
Symbol Selection:
This allows you to select the second asset to compare with the chart's primary asset
Default is Apple (NASDAQ:AAPL), but you can change this to any symbol
Example: If you're viewing a Bitcoin chart, you might set this to "NASDAQ:TSLA" to see if Bitcoin and Tesla are correlated
Correlation Window (60): This is the number of periods used to calculate the main correlation
Larger values (e.g., 100-500) provide more stable, long-term correlation measures
Smaller values (e.g., 10-50) are more responsive to recent price movements
60 is a good balance for most daily charts (about 3 months of trading days)
Rolling Correlation Window (20): A shorter window to detect recent changes in correlation
This helps identify when the relationship between assets is strengthening or weakening
Default of 20 is roughly one month of trading days
Return Type: This determines how price changes are calculated
Simple Returns: (Today's Price - Yesterday's Price) / Yesterday's Price
Easy to understand: "The asset went up 2% today"
Log Returns: Natural logarithm of (Today's Price / Yesterday's Price)
More mathematically elegant for statistical analysis
Better for time-additive properties (returns over multiple periods)
Less sensitive to extreme values.
Confidence Level (95%): This determines how certain we want to be about our results
95% confidence means we accept a 5% chance of being wrong (false positive)
Higher confidence (e.g., 99%) makes the test more strict
Lower confidence (e.g., 90%) makes the test more lenient
95% is the standard in most scientific research
Show Statistical Significance: When enabled, the script will test if the correlation is statistically significant or just due to random chance.
Display options control what you see on the chart:
Show Pearson/Spearman/Rolling Correlation: Toggle each correlation type on/off
Show Scatter Plot: Displays a scatter plot of returns (limited to recent points to avoid performance issues)
Show Statistical Tests: Enables the detailed statistics table
Table Text Size: Adjusts the size of text in the statistics table
2.Functions explained-
calcReturns():
This function calculates price returns based on your selected method:
Log Returns:
Formula: ln(Price_t / Price_t-1)
Example: If a stock goes from $100 to $101, the log return is ln(101/100) = ln(1.01) ≈ 0.00995 or 0.995%
Benefits: More symmetric, time-additive, and better for statistical modeling
Simple Returns:
Formula: (Price_t - Price_t-1) / Price_t-1
Example: If a stock goes from $100 to $101, the simple return is (101-100)/100 = 0.01 or 1%
Benefits: More intuitive and easier to understand
rankArray():
This function calculates the rank of each value in an array, which is used for Spearman correlation:
How ranking works:
The smallest value gets rank 1
The second smallest gets rank 2, and so on
For ties (equal values), they get the average of their ranks
Example: For values
Sorted:
Ranks: (the two 2s tie for ranks 1 and 2, so they both get 1.5)
Why this matters: Spearman correlation uses ranks instead of actual values, making it less sensitive to outliers and non-linear relationships.
pearsonCorr():
This function calculates the Pearson correlation coefficient:
Mathematical Formula:
r = (nΣxy - ΣxΣy) / √
Where x and y are the two variables, and n is the sample size
What it measures:
The strength and direction of the linear relationship between two variables
Values range from -1 (perfect negative linear relationship) to +1 (perfect positive linear relationship)
0 indicates no linear relationship
Example:
If two stocks have a Pearson correlation of 0.8, they have a strong positive linear relationship
When one stock goes up, the other tends to go up in a fairly consistent proportion
spearmanCorr():
This function calculates the Spearman rank correlation:
How it works:
Convert each value in both datasets to its rank
Calculate the Pearson correlation on the ranks instead of the original values
What it measures:
The strength and direction of the monotonic relationship between two variables
A monotonic relationship is one where as one variable increases, the other either consistently increases or decreases
It doesn't require the relationship to be linear
When to use it instead of Pearson:
When the relationship is monotonic but not linear
When there are significant outliers in the data
When the data is ordinal (ranked) rather than interval/ratio
Example:
If two stocks have a Spearman correlation of 0.7, they have a strong positive monotonic relationship
When one stock goes up, the other tends to go up, but not necessarily in a straight-line relationship
tStatistic():
This function calculates the t-statistic for correlation:
Mathematical Formula: t = r × √((n-2)/(1-r²))
Where r is the correlation coefficient and n is the sample size
What it measures:
How many standard errors the correlation is away from zero
Used to test the null hypothesis that the true correlation is zero
Interpretation:
Larger absolute t-values indicate stronger evidence against the null hypothesis
Generally, a t-value greater than 2 (in absolute terms) is considered statistically significant at the 95% confidence level
criticalT() and pValue():
These functions provide approximations for statistical significance testing:
criticalT():
Returns the critical t-value for a given degrees of freedom (df) and significance level
The critical value is the threshold that the t-statistic must exceed to be considered statistically significant
Uses approximations since Pine Script doesn't have built-in statistical distribution functions
pValue():
Estimates the p-value for a given t-statistic and degrees of freedom
The p-value is the probability of observing a correlation as strong as the one calculated, assuming the true correlation is zero
Smaller p-values indicate stronger evidence against the null hypothesis
Standard interpretation:
p < 0.01: Very strong evidence (marked with **)
p < 0.05: Strong evidence (marked with *)
p ≥ 0.05: Weak evidence, not statistically significant
stdev():
This function calculates the standard deviation of a dataset:
Mathematical Formula: σ = √(Σ(x-μ)²/(n-1))
Where x is each value, μ is the mean, and n is the sample size
What it measures:
The amount of variation or dispersion in a set of values
A low standard deviation indicates that the values tend to be close to the mean
A high standard deviation indicates that the values are spread out over a wider range
Why it matters for correlation:
Standard deviation is used in calculating the correlation coefficient
It also provides information about the volatility of each asset's returns
Comparing standard deviations helps understand the relative riskiness of the two assets.
3.Getting Price Data-
price1: The closing price of the primary asset (the chart you're viewing)
price2: The closing price of the secondary asset (the one you selected in the input parameters)
Returns are used instead of raw prices because:
Returns are typically stationary (mean and variance stay constant over time)
Returns normalize for price levels, allowing comparison between assets of different values
Returns represent what investors actually care about: percentage changes in value
4.Information Table-
Creates a table to display statistics
Only shows on the last bar to avoid performance issues
Positioned in the top right of the chart
Has 2 columns and 15 rows
Populating the Table
The script then populates the table with various statistics:
Header Row: "Metric" and "Value"
Sample Information: Sample size and return type
Pearson Correlation: Value, t-statistic, p-value, and significance
Spearman Correlation: Value, t-statistic, p-value, and significance
Rolling Correlation: Current value
Standard Deviations: For both assets
Interpretation: Text description of the correlation strength
The table uses color coding to highlight important information:
Green for significant positive results
Red for significant negative results
Yellow for borderline significance
Color-coded headers for each section
=> Practical Applications and Interpretation
How to Interpret the Results
Correlation Strength
0.0 to 0.3 (or 0.0 to -0.3): Weak or no correlation
The assets move mostly independently of each other
Good for diversification purposes
0.3 to 0.7 (or -0.3 to -0.7): Moderate correlation
The assets show some tendency to move together (or in opposite directions)
May be useful for certain trading strategies but not extremely reliable
0.7 to 1.0 (or -0.7 to -1.0): Strong correlation
The assets show a strong tendency to move together (or in opposite directions)
Can be useful for pairs trading, hedging, or as a market indicator
Statistical Significance
p < 0.01: Very strong evidence that the correlation is real
Marked with ** in the table
Very unlikely to be due to random chance
p < 0.05: Strong evidence that the correlation is real
Marked with * in the table
Unlikely to be due to random chance
p ≥ 0.05: Weak evidence that the correlation is real
Not marked in the table
Could easily be due to random chance
Rolling Correlation
The rolling correlation shows how the relationship between assets changes over time
If the rolling correlation is much different from the long-term correlation, it suggests the relationship is changing
This can indicate:
A shift in market regime
Changing fundamentals of one or both assets
Temporary market dislocations that might present trading opportunities
Trading Applications
1. Portfolio Diversification
Goal: Reduce overall portfolio risk by combining assets that don't move together
Strategy: Look for assets with low or negative correlations
Example: If you hold tech stocks, you might add some utilities or bonds that have low correlation with tech
2. Pairs Trading
Goal: Profit from the relative price movements of two correlated assets
Strategy:
Find two assets with strong historical correlation
When their prices diverge (one goes up while the other goes down)
Buy the underperforming asset and short the outperforming asset
Close the positions when they converge back to their normal relationship
Example: If Coca-Cola and Pepsi are highly correlated but Coca-Cola drops while Pepsi rises, you might buy Coca-Cola and short Pepsi
3. Hedging
Goal: Reduce risk by taking an offsetting position in a negatively correlated asset
Strategy: Find assets that tend to move in opposite directions
Example: If you hold a portfolio of stocks, you might buy some gold or government bonds that tend to rise when stocks fall
4. Market Analysis
Goal: Understand market dynamics and interrelationships
Strategy: Analyze correlations between different sectors or asset classes
Example:
If tech stocks and semiconductor stocks are highly correlated, movements in one might predict movements in the other
If the correlation between stocks and bonds changes, it might signal a shift in market expectations
5. Risk Management
Goal: Understand and manage portfolio risk
Strategy: Monitor correlations to identify when diversification benefits might be breaking down
Example: During market crises, many assets that normally have low correlations can become highly correlated (correlation convergence), reducing diversification benefits
Advanced Interpretation and Caveats
Correlation vs. Causation
Important Note: Correlation does not imply causation
Example: Ice cream sales and drowning incidents are correlated (both increase in summer), but one doesn't cause the other
Implication: Just because two assets move together doesn't mean one causes the other to move
Solution: Look for fundamental economic reasons why assets might be correlated
Non-Stationary Correlations
Problem: Correlations between assets can change over time
Causes:
Changing market conditions
Shifts in monetary policy
Structural changes in the economy
Changes in the underlying businesses
Solution: Use rolling correlations to monitor how relationships change over time
Outliers and Extreme Events
Problem: Extreme market events can distort correlation measurements
Example: During a market crash, many assets may move in the same direction regardless of their normal relationship
Solution:
Use Spearman correlation, which is less sensitive to outliers
Be cautious when interpreting correlations during extreme market conditions
Sample Size Considerations
Problem: Small sample sizes can produce unreliable correlation estimates
Rule of Thumb: Use at least 30 data points for a rough estimate, 60+ for more reliable results
Solution:
Use the default correlation length of 60 or higher
Be skeptical of correlations calculated with small samples
Timeframe Considerations
Problem: Correlations can vary across different timeframes
Example: Two assets might be positively correlated on a daily basis but negatively correlated on a weekly basis
Solution:
Test correlations on multiple timeframes
Use the timeframe that matches your trading horizon
Look-Ahead Bias
Problem: Using information that wouldn't have been available at the time of trading
Example: Calculating correlation using future data
Solution: This script avoids look-ahead bias by using only historical data
Best Practices for Using This Script
1. Appropriate Parameter Selection
Correlation Window:
For short-term trading: 20-50 periods
For medium-term analysis: 50-100 periods
For long-term analysis: 100-500 periods
Rolling Window:
Should be shorter than the main correlation window
Typically 1/3 to 1/2 of the main window
Return Type:
For most applications: Log Returns (better statistical properties)
For simplicity: Simple Returns (easier to interpret)
2. Validation and Testing
Out-of-Sample Testing:
Calculate correlations on one time period
Test if they hold in a different time period
Multiple Timeframes:
Check if correlations are consistent across different timeframes
Economic Rationale:
Ensure there's a logical reason why assets should be correlated
3. Monitoring and Maintenance
Regular Review:
Correlations can change, so review them regularly
Alerts:
Set up alerts for significant correlation changes
Documentation:
Keep notes on why certain assets are correlated and what might change that relationship
4. Integration with Other Analysis
Fundamental Analysis:
Combine correlation analysis with fundamental factors
Technical Analysis:
Use correlation analysis alongside technical indicators
Market Context:
Consider how market conditions might affect correlations
Conclusion
This Scientific Correlation Testing Framework provides a comprehensive tool for analyzing relationships between financial assets. By offering both Pearson and Spearman correlation methods, statistical significance testing, and rolling correlation analysis, it goes beyond simple correlation measures to provide deeper insights.
For beginners, this script might seem complex, but it's built on fundamental statistical concepts that become clearer with use. Start with the default settings and focus on interpreting the main correlation lines and the statistics table. As you become more comfortable, you can adjust the parameters and explore more advanced applications.
Remember that correlation analysis is just one tool in a trader's toolkit. It should be used in conjunction with other forms of analysis and with a clear understanding of its limitations. When used properly, it can provide valuable insights for portfolio construction, risk management, and pair trading strategy development.
MA Cloud + Linha Média🧠 Description of “MA Cloud + Average Line” Indicator
This Pine Script indicator combines multiple moving averages (MAs) into a dynamic visualization that helps traders identify market trends, momentum shifts, and trend strength. It creates a colored cloud between the fastest and slowest moving averages, and also plots an average line representing the mean of all active MAs.
⚙️ 1. Core Features
Multiple Moving Averages (MAs)
Supports up to four customizable moving averages (MA1, MA2, MA3, MA4).
Each MA can use different types:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
VWMA (Volume-Weighted Moving Average)
RMA (Smoothed Moving Average)
Hull MA (Hull Moving Average)
LSMA (Least Squares Moving Average)
The trader can define each MA’s period, color, and choose whether it’s active or not.
Trend Color Coding
Each MA changes color based on its slope:
Green (or chosen “Up Color”) when rising
Red (or chosen “Down Color”) when falling
This gives instant visual feedback on short-term direction.
MA Cloud (Trend Zone)
When the “Cloud” is active, the area between the minimum and maximum of all active MAs is shaded.
The cloud changes color based on alignment:
🟩 Green Cloud – all MAs are aligned upward (strong bullish trend).
🟥 Red Cloud – all MAs are aligned downward (strong bearish trend).
⚪ Gray Cloud – mixed alignment (no clear trend / consolidation).
Average Line (Mean of All MAs)
Calculates the average of all active MAs and plots it as a central “mean” line.
Serves as a dynamic trend guide — when price is above it, the market tends to be bullish; below it, bearish.
The color of the line follows the current cloud color for consistency.
📈 2. How It Helps Identify Trends
This indicator provides multiple layers of trend confirmation:
Visual Element Interpretation Trend Insight
MA Slope Color Green (Up) / Red (Down) Short-term momentum direction
MA Cloud Color Green / Red / Gray Overall trend alignment across timeframes
Average Line Mean of all MAs Acts as a “trend equilibrium” line
Price vs. Average Line Above = Bullish / Below = Bearish Confirms trend bias
🔍 3. Example Use Cases
Trend Following
Enter long trades when all MAs are aligned (Cloud = Green) and price is above the average line.
Enter short trades when the Cloud is Red and price is below the average line.
Trend Strength Confirmation
The wider the distance between MAs (thicker cloud), the stronger the ongoing trend.
A narrowing cloud or color shift (green → gray → red) can warn of trend reversal or consolidation.
Dynamic Support and Resistance
The MA Cloud acts as a support zone in uptrends and resistance zone in downtrends.
Traders can use the edges of the cloud to identify possible pullback entry zones.
Multi-Timeframe Analysis
By using fast MAs (e.g., 20/50) and slow MAs (100/200), traders can visualize short-term vs. long-term trend interaction, similar to “Golden Cross” and “Death Cross” setups.
🧩 4. How to Use It Practically
Step 1: Enable only the MAs you need (e.g., 20, 50, 200).
Step 2: Observe the cloud color:
🟩 Green → Favor long trades
🟥 Red → Favor short trades
⚪ Gray → Wait for confirmation
Step 3: Use the average line as a filter:
Trade only in the direction of the average line’s slope.
Step 4: Combine with volume, RSI, or price action to refine entries.
💬 Summary
Indicator Name: MA Cloud + Average Line
Purpose: Visual trend detection and confirmation
Best For: Swing and trend-following traders
Signals Provided:
Trend alignment (via color-coded cloud)
Momentum shifts (via MA color changes)
Dynamic support/resistance (via cloud zones)
Overall trend bias (via average line)
RRG Sector Snapshot RRG Sector Snapshot · Clear UI — User Guide
What this indicator does
Purpose: Visualize sector rotation by comparing each sector’s Relative Strength (RS-Ratio) and RS-Momentum versus a benchmark (e.g., VNINDEX).
Output: A quadrant map (table overlay) that positions each sector into one of four regimes:
LEADING (top-right): Strong and accelerating — leadership zone.
WEAKENING (bottom-right): Strong but decelerating — may be topping or consolidating.
LAGGING (bottom-left): Weak and decelerating — avoid unless mean-reverting.
IMPROVING (top-left): Weak but accelerating — candidates for next rotation into leadership.
How it works (under the hood)
X-axis (Strength): RS-Ratio = Sector Close / Benchmark Close, then normalized with a Z-Score over a lookback (normLen).
Y-axis (Momentum): Linear-regression slope of RS-Ratio over rsLen, then normalized with a Z-Score (normLen).
Mapping to grid: Both axes are Z-Scores scaled to a square grid (rrgSize × rrgSize) using a zoom factor (rrgScale). The center is neutral (0,0). Momentum increases upward (Y=0 is the top row in the table).
Quick start (3 minutes)
Add to chart:
TradingView → Pine Editor → paste the script → Save → Add to chart.
Set a benchmark: In inputs, choose Benchmark (X axis) — default INDEX:VNINDEX. Use VN30 or another index if it better reflects your universe.
Load sectors: Fill S1..S10 with sector or index symbols you track (up to 10). Set Slots to Use to the number you actually use.
Adjust view:
rrgSize (grid cells): 18–24 is a good starting point.
rrgScale (zoom): 2.5–3.5 typically; decrease to “zoom out” (points cluster near center), increase to “zoom in” (points spread to edges).
Read the map:
Prioritize sectors in LEADING; shortlist sectors in IMPROVING (could rotate into LEADING).
WEAKENING often marks late-cycle strength; LAGGING is typically avoid.
Inputs — what they do and how to change them
General
Analysis TF: Timeframe used to compute RRG (can be different from chart’s TF). Daily for swing, 1H/4H for tactical rotation, Weekly for macro view.
Benchmark (X axis): The index used for RS baseline (e.g., INDEX:VNINDEX, INDEX:VN30, major ETFs, or a custom composite).
RRG Calculation
RS Lookback (rsLen): Bars used for slope of RS (momentum).
Daily: 30–60 (default 40)
Intraday (1H/4H): 20–40
Weekly: 26–52
Normalization Lookback (Z-Score) (normLen): Window for Z-Score on both axes.
Daily: 80–120 (default 100)
Intraday: 40–80
Weekly: 52–104
Tip: Shorter lookbacks = more responsive but noisier; longer = smoother but slower.
RRG HUD (Table)
Show RRG Snapshot (rrgEnable): Toggle the table on/off.
Position (rrgPos): top_right | top_left | bottom_right | bottom_left.
Grid Size (Cells) (rrgSize): Table dimensions (N×N). Larger = more resolution but takes more space.
Z-Scale (Zoom) (rrgScale): Maps Z-Scores to the grid.
Smaller (2.0–2.5): Zoom out (more points near center).
Larger (3.5–4.0): Zoom in (emphasize outliers).
Appearance
Tag length (tagLen): Characters per sector tag. Use 4–6 for clarity.
Text size (textSizeOp): Tiny | Small | Normal | Large. Use Large for presentation screens or dense lists.
Axis thickness (axisThick): 1 = thin axis; 2 = thicker double-strip axis.
Quadrant alpha (bgAlpha): Transparency of quadrant backgrounds. 80–90 makes text pop.
Sectors (Max 10)
Slots to Use (sectorSlots): How many sector slots are active (≤10).
S1..S10: Each slot is a symbol (index, sector index, or ETF). Replace defaults to fit your market/universe.
How to interpret the map
Quadrants:
Leading (top-right): Relative strength above average and improving — trend-follow candidates.
Weakening (bottom-right): Still strong but momentum cooling — watch for distribution or pauses.
Lagging (bottom-left): Underperforming and still losing momentum — avoid unless doing mean-reversion.
Improving (top-left): Early recovery — candidates to transition into Leading if the move persists.
Overlapping sectors in one cell: The indicator shows “TAG +n” where TAG is the first tag, +n is the number of additional sectors sharing that cell. If many overlap:
Increase rrgSize, or
Decrease rrgScale to zoom out, or
Reduce Slots to Use to a smaller selection.
Suggested workflows
Daily swing
Benchmark: VNINDEX or VN30
rsLen 40–60, normLen 100–120, rrgSize 18–24, rrgScale 2.5–3.5
Routine:
Identify Leading sectors (top-right).
Spot Improving sectors near the midline moving toward top-right.
Confirm with price/volume/breakout on sector charts or top components.
Intraday (1H/4H) tactical
rsLen 20–40, normLen 60–100, rrgScale 2.0–3.0
Expect faster rotations and more noise; tighten filters with your own entry rules.
Weekly (macro rotation)
rsLen 26–52, normLen 52–104, rrgScale 3.0–4.0
Great for portfolio tilts and sector allocation.
Tuning tips
If everything clusters near center: Increase rrgScale (zoom in) or reduce normLen (more contrast).
If points are too spread: Decrease rrgScale (zoom out) or increase normLen (smoother normalization).
If the table is too big/small: Change rrgSize (cells).
If tags are hard to read: Increase textSizeOp to Large, tagLen to 5–6, and consider bgAlpha ~80–85.
Troubleshooting
No table on chart:
Ensure Show RRG Snapshot is enabled.
Change Position to a different corner.
Reduce Grid Size if the table exceeds the chart area.
Many sectors “missing”:
They’re likely overlapping in the same cell; the cell will show “TAG +n”.
Increase rrgSize, decrease rrgScale, or reduce Slots to Use.
Early bars show nothing:
You need enough data for rsLen and normLen. Scroll back or reduce lookbacks temporarily.
Best practices
Use RRG for context and rotation scouting, then confirm with your execution tools (trend structure, breakouts, volume, risk metrics).
Benchmark selection matters. If most of your watchlist tracks VN30, use INDEX:VN30 as the benchmark to get a truer relative read.
Revisit settings per timeframe. Intraday needs more responsiveness (shorter lookbacks, smaller Z-Scale); weekly needs stability (longer lookbacks, larger Z-Scale).
FAQ
Can I use ETFs or custom indices as sectors? Yes. Any symbol supported by TradingView works.
Can I track individual stocks instead of sectors? Yes (up to 10); just replace the S1..S10 symbols.
Why Z-Score? It standardizes each axis to “how unusual” the value is versus its own history — more robust than raw ratios across different scales.
[ i]
How to Set Up (Your Market Template)
This is the most important part for customizing the indicator to any market.
Step 1: Choose Your TF & Benchmark
Open the indicator's Settings.
Analysis TF: Set the timeframe you want to analyze (e.g., D for medium-term, W for long-term).
Benchmark (Trục X): This is the index you want to compare against.
Vietnamese Market: Leave the default INDEX:VNINDEX.
US Market: Change to SP:SPX or NASDAQ:NDX.
Crypto Market: Change to TOTAL (entire market cap) or BTC.D (Bitcoin Dominance).
Step 2: Input Your "Universe" (The 10 Slots)
This is where you decide what to track. You have 10 slots (S1 to S10).
For Vietnamese Sectors (Default):
Leave the default sector codes like INDEX:VNFINLEAD (Finance), INDEX:VNREAL (Real Estate), INDEX:VNIND (Industry), etc.
Template for Crypto "Sectors":
S1: BTC.D
S2: ETH.D
S3: TOTAL2 (Altcoin Market Cap)
S4: TOTAL.DEFI (DeFi)
S5: CRYPTOCAP:GAME (GameFi)
...and so on.
Template for Blue Chip Stocks:
Benchmark: INDEX:VN30
S1: HOSE:FPT
S2: HOSE:VCB
S3: HOSE:HPG
S4: HOSE:MWG
...and so on.
Template for Commodities:
Benchmark: TVC:DXY (US Dollar Index)
S1: TVC:GOLD
S2: TVC:USOIL
S3: TVC:SILVER
S4: COMEX:HG1! (Copper)
...and so on.
Step 3: Fine-Tuning
RS Lookback: A larger number (e.g., 100) gives a smoother, long-term view. A smaller number (e.g., 20) is more sensitive to short-term changes.
Z-Scale (Zoom): This is the "magnification" of the map.
If all your sectors are crowded in the middle, increase this number (e.g., 4.0) to "zoom in."
If your sectors are stuck on the edges, decrease this number (e.g., 2.0) to "zoom out."
Tag length: How many letters to display for the ticker (e.g., 4 will show VNFI).
My Rate Of Change. Buy equities if crosses up from 0, Sell equities and switch to commodities like Gold if crosses down 40
Advanced Psychological Levels with Dynamic Spacing═══════════════════════════════════════
ADVANCED PSYCHOLOGICAL LEVELS WITH DYNAMIC SPACING
═══════════════════════════════════════
A comprehensive psychological price level indicator that automatically identifies and displays round number levels across multiple timeframes. Features dynamic ATR-based spacing, smart crypto detection, distance tracking, and customizable alert system.
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WHAT THIS INDICATOR DOES
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This indicator automatically draws psychological price levels (round numbers) that often act as support and resistance:
- Dynamic ATR-Based Spacing - Adapts level spacing to market volatility
- Multiple Level Types - Major (250 pip), Standard (100 pip), Mid, and Intraday levels
- Smart Asset Detection - Automatically adjusts for Forex, Crypto, Indices, and CFDs
- Crypto Price Adaptation - Intelligent level spacing based on cryptocurrency price magnitude
- Distance Information Table - Real-time percentage distance to nearest levels
- Combined Level Labels - Clear identification when multiple level types coincide
- Performance Optimized - Configurable visible range and label limits
- Comprehensive Alerts - Notifications when price crosses any level type
───────────────────────────────────────
HOW IT WORKS
───────────────────────────────────────
PSYCHOLOGICAL LEVELS CONCEPT:
Psychological levels are round numbers where traders tend to place orders, creating natural support and resistance zones. These include:
- Forex: 1.0000, 1.0100, 1.0050 (pips)
- Crypto: $100, $1,000, $10,000 (whole numbers)
- Indices: 10,000, 10,500, 11,000 (points)
Why They Matter:
- Traders naturally gravitate to round numbers
- Stop losses cluster at these levels
- Take profit orders concentrate here
- Institutional algorithmic trading often targets these levels
DYNAMIC ATR-BASED SPACING:
Traditional Method:
- Fixed spacing regardless of volatility
- May be too tight in volatile markets
- May be too wide in quiet markets
Dynamic Method (Recommended):
- Uses ATR (Average True Range) to measure volatility
- Automatically adjusts level spacing
- Tighter levels in low volatility
- Wider levels in high volatility
Calculation:
1. Calculate ATR over specified period (default: 14)
2. Multiply by ATR multiplier (default: 2.0)
3. Round to nearest psychological level
4. Generate levels at dynamic intervals
Benefits:
- Adapts to market conditions
- More relevant levels in all volatility regimes
- Reduces clutter in trending markets
- Provides more detail in ranging markets
LEVEL TYPES:
Major Levels (250 pip/point):
- Highest significance
- Primary support/resistance zones
- Color: Red (default)
- Style: Solid lines
- Spacing: 2.5x standard step
Standard Levels (100 pip/point):
- Secondary importance
- Common psychological barriers
- Color: Blue (default)
- Style: Dashed lines
- Spacing: Standard step
Mid Levels (50% between major):
- Optional intermediate levels
- Halfway between major levels
- Color: Gray (default)
- Style: Dotted lines
- Usage: Additional confluence points
Intraday Levels (sub-100 pip):
- For intraday traders
- Fine-grained precision
- Color: Yellow (default)
- Style: Dotted lines
- Only shown on intraday timeframes
SMART ASSET DETECTION:
Forex Pairs:
- Detects major currency pairs automatically
- Uses pip-based calculations
- Standard: 100 pips (0.0100)
- Major: 250 pips (0.0250)
- Intraday: 20, 50, 80 pip subdivisions
Cryptocurrencies:
- Automatic price magnitude detection
- Adaptive spacing based on price:
* Under $0.10: Levels at $0.01, $0.05
* $0.10-$1: Levels at $0.10, $0.50
* $1-$10: Levels at $1, $5
* $10-$100: Levels at $10, $50
* $100-$1,000: Levels at $100, $500
* $1,000-$10,000: Levels at $1,000, $5,000
* Over $10,000: Levels at $5,000, $10,000
Indices & CFDs:
- Fixed point-based system
- Major: 500 point intervals (with 250 sub-levels)
- Standard: 100 point intervals
- Suitable for stock indices like SPX, NASDAQ
COMBINED LEVEL LABELS:
When multiple level types coincide at the same price:
- Single line drawn (highest priority color)
- Combined label shows all types
- Priority: Major > Standard > Mid > Intraday
Example Label Formats:
- "1.1000 Major" - Major level only
- "1.1000 Std + Major" - Both standard and major
- "50000 Intra + Mid + Std" - Three levels coincide
Benefits:
- Cleaner chart appearance
- Clear identification of confluence
- Reduced visual clutter
- Easy to spot high-importance levels
DISTANCE INFORMATION TABLE:
Real-time tracking of nearest levels:
Table Contents:
- Nearest major level above (price and % distance)
- Nearest standard level above (price and % distance)
- Nearest standard level below (price and % distance)
Display:
- Top right corner (configurable)
- Color-coded by level type
- Real-time percentage calculations
- Helpful for position management
Usage:
- Identify proximity to key levels
- Set realistic profit targets
- Gauge potential move magnitude
- Monitor approaching resistance/support
ALERT SYSTEM:
Comprehensive crossing alerts:
Alert Types:
- Major Level Crosses
- Standard Level Crosses
- Intraday Level Crosses
Alert Modes:
- First Cross Only: Alert once when level is crossed
- All Crosses: Alert every time level is crossed
Alert Information:
- Level type crossed
- Specific price level
- Direction (above/below)
- One alert per bar to prevent spam
Configuration:
- Enable/disable by level type
- Choose alert frequency
- Customize for your trading style
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HOW TO USE
───────────────────────────────────────
INITIAL SETUP:
General Settings:
1. Enable "Use Dynamic ATR-Based Spacing" (recommended)
2. Set ATR Period (14 is standard)
3. Adjust ATR Multiplier (2.0 is balanced)
Visibility Settings:
1. Set Visible Range % (10% recommended for clarity)
2. Adjust Label Offset for readability
3. Configure performance limits if needed
Level Selection:
1. Enable/disable level types based on trading style
2. Adjust line counts for each type
3. Choose line styles and colors for visibility
TRADING STRATEGIES:
Breakout Trading:
1. Wait for price to approach major or standard level
2. Monitor for consolidation near level
3. Enter on confirmed break above/beyond level
4. Stop loss just beyond the broken level
5. Target: Next major or standard level
Rejection Trading:
1. Identify major psychological level
2. Wait for price to test the level
3. Look for rejection signals (wicks, bearish/bullish candles)
4. Enter in direction of rejection
5. Stop beyond the level
6. Target: Previous level or mid-level
Range Trading:
1. Identify range between two major levels
2. Buy at lower psychological level
3. Sell at upper psychological level
4. Use standard and mid-levels for position management
5. Exit if major level breaks with volume
Confluence Trading:
1. Look for combined levels (Std + Major)
2. These represent high-probability zones
3. Use as primary support/resistance
4. Increase position size at confluence
5. Expect stronger reactions at these levels
Session-Based Trading:
1. Note opening level at session start (Asian/London/NY)
2. Trade breakouts of major levels during high-volume sessions
3. London/NY sessions: More likely to break levels
4. Asian session: More likely to respect levels (range trading)
RISK MANAGEMENT WITH PSYCHOLOGICAL LEVELS:
Stop Loss Placement:
- Place stops just beyond psychological levels
- Add buffer (5-10 pips for forex)
- Avoid exact round numbers (stop hunting risk)
- Use previous major level as maximum stop
Take Profit Strategy:
- First target: Next standard level (partial profit)
- Second target: Next major level (remaining position)
- Trail stops to breakeven at first target
- Use distance table to calculate risk/reward
Position Sizing:
- Larger positions at major levels (higher probability)
- Smaller positions at intraday levels (lower probability)
- Scale in at standard levels between major levels
- Reduce size when multiple levels are close together
TIMEFRAME CONSIDERATIONS:
Higher Timeframes (4H, Daily, Weekly):
- Focus on Major and Standard levels only
- Disable Intraday and Mid levels
- Wider level spacing expected
- Use for swing trading and position trading
Lower Timeframes (5m, 15m, 1H):
- Enable all level types
- Use Intraday levels for precision
- Tighter level spacing acceptable
- Good for day trading and scalping
Multi-Timeframe Approach:
- Identify major levels on Daily/4H charts
- Refine entries using 15m/1H intraday levels
- Trade in direction of higher timeframe bias
- Use lower timeframe levels for position management
───────────────────────────────────────
CONFIGURATION GUIDE
───────────────────────────────────────
GENERAL SETTINGS:
Dynamic ATR-Based Spacing:
- Enabled: Recommended for most markets
- Disabled: Fixed psychological levels
- ATR Period: 14 (standard), 10 (responsive), 20 (smooth)
- ATR Multiplier: 1.0-5.0 (2.0 is balanced)
VISIBILITY SETTINGS:
Visible Range %:
- 5%: Very tight range, minimal clutter
- 10%: Balanced view (recommended)
- 20%: Wide range, more context
- 50%: Maximum range, all levels visible
Label Offset:
- 10-20 bars: Close to current price
- 30-50 bars: Moderate distance
- 50-100 bars: Far from price action
Performance Limits:
- Max Historical Bars: Reduce if indicator loads slowly
- Max Labels: Reduce for cleaner chart (20-30 recommended)
LEVEL CUSTOMIZATION:
Line Count:
- Lower (1-3): Cleaner chart, fewer levels
- Medium (4-6): Balanced view
- Higher (7-10): More context, busier chart
Line Styles:
- Solid: High importance, easy to see
- Dashed: Medium importance, clear but subtle
- Dotted: Low importance, minimal visual weight
Colors:
- Use contrasting colors for different level types
- Red/Blue/Yellow default works well
- Adjust based on chart background and personal preference
DISTANCE TABLE:
Position:
- Top Right: Doesn't interfere with price action
- Top Left: Good for right-side price scale
- Bottom positions: Less common but available
Colors:
- Default (white text, dark background) works for most charts
- Match your chart theme for consistency
- Ensure text is readable against background
ALERT CONFIGURATION:
Alert by Level Type:
- Major: Most important, fewer false signals
- Standard: Balance of frequency and importance
- Intraday: Many signals, best for active traders
Alert Frequency:
- First Cross Only: Cleaner, less noise (recommended for swing trading)
- All Crosses: Every touch, good for scalping
Alert Setup in TradingView:
1. Configure desired alert types in indicator settings
2. Right-click chart → Add Alert
3. Select this indicator
4. Choose "Any alert() function call"
5. Set delivery method (mobile, email, webhook)
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ASSET-SPECIFIC TIPS
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FOREX (EUR/USD, GBP/USD, etc.):
- Major levels at x.x000, x.x500
- Standard levels at x.xx00
- Intraday levels at 20/50/80 pips
- Most effective during London/NY sessions
- Watch for "figure" levels (1.0000, 1.1000)
CRYPTOCURRENCIES (BTC, ETH, etc.):
- Enable dynamic spacing for volatile markets
- Levels adjust automatically based on price
- Watch major $1,000 increments for BTC
- $100 levels important for ETH
- Smaller caps: Use standard levels
- High volatility: Increase ATR multiplier to 3.0
STOCK INDICES (SPX, NASDAQ, etc.):
- 100-point levels most important
- 500-point levels for major S/R
- 50-point mid-levels for refinement
- Watch end-of-day for level reactions
- Futures often lead spot on level breaks
GOLD/COMMODITIES:
- Major levels at $50 increments ($1,900, $1,950)
- Standard levels at $10 increments
- Very reactive to psychological levels
- Watch for false breaks during low volume
- Best reactions during active trading hours
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BEST PRACTICES
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Chart Setup:
- Use clean price action charts
- Avoid too many indicators
- Ensure psychological levels are clearly visible
- Match colors to your chart theme
Level Selection:
- Start with Major and Standard levels only
- Add Mid and Intraday as needed
- Less is more - avoid chart clutter
- Adjust based on timeframe
Combining with Other Tools:
- Volume profile for confluence
- Trendlines intersecting psychological levels
- Moving averages near round numbers
- Fibonacci levels coinciding with psychological levels
Common Mistakes to Avoid:
- Trading every level touch (be selective)
- Ignoring volume confirmation
- Setting stops exactly at levels (stop hunting)
- Forgetting to adjust for different assets
- Over-relying on levels without price action confirmation
Performance Optimization:
- Reduce visible range for faster loading
- Lower max historical bars on lower timeframes
- Limit labels to 30-50 for clarity
- Disable unused level types
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EDUCATIONAL DISCLAIMER
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This indicator identifies psychological price levels based on round numbers that tend to act as support and resistance. The methodology includes:
- Round number detection algorithms
- ATR-based dynamic spacing calculations
- Asset-specific level determination
- Distance percentage calculations
Psychological levels are a recognized concept in technical analysis, studied by traders and institutions. However, they do not guarantee price reactions and should be used as part of a comprehensive trading strategy including proper risk management, volume analysis, and price action confirmation.
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USAGE DISCLAIMER
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This tool is for educational and analytical purposes. Psychological levels can act as support or resistance but price reactions are not guaranteed. Dynamic spacing may generate different levels in different market conditions. Always conduct independent analysis, use proper risk management, and never risk capital you cannot afford to lose. Past performance does not indicate future results.
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CREDITS & ATTRIBUTION
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Original Concept: Sonar Lab
Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM):
Phase Coherence Detection Through Complex-Plane Oscillator Analysis
Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge.
The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions.
What Makes This Original
Complex-Plane Phasor Framework
This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation.
From these components, the system extracts:
Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°)
Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction
This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory).
Coherence Index Calculation
The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ).
The CI measures what happens when you sum all these vectors:
Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ)
Coherence Index : CI = |R| / N
Where |R| is the magnitude of the resultant vector and N is the number of active oscillators.
The CI ranges from 0 to 1:
CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference
CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference
0 < CI < 1 : Partial alignment—some clustering with some scatter
This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss.
Dominant Phase and Direction Detection
Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points:
Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ))
This gives the "average direction" of all oscillator phases, mapped to -180° to +180°:
+90° to -90° (right half-plane): Bullish phase dominance
+90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance
The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging.
Entanglement Matrix and Pairwise Coherence
While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates:
E(i,j) = |cos(φᵢ - φⱼ)|
This represents the phase agreement between oscillators i and j:
E = 1.0 : Oscillators are in-phase (0° or 360° apart)
E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal)
E between 0 and 1 : Varying degrees of alignment
The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered.
The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently.
Phase-Lock Tolerance Mechanism
A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators:
For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180°
Max Spread = maximum Δφ across all pairs
If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band.
This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals.
Multi-Layer Visual Architecture
QRFM includes six visual components that represent the same underlying mathematics from different perspectives:
Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it.
Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition.
Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier.
Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers.
Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down.
Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%).
Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match.
Core Components and How They Work Together
1. Oscillator Normalization Engine
The foundation is creating a common measurement scale. QRFM supports eight oscillators:
RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors
MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to
Stochastic %K : Normalized from using (80, 20) anchors
CCI : Divided by 200 (typical extreme level), clamped to
Williams %R : Normalized from using (-20, -80) anchors
MFI : Normalized from using (80, 20) anchors
ROC : Divided by 10, clamped to
TSI : Divided by 50, clamped to
Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI.
2. Analytic Signal Construction
For each active oscillator at each bar, the system constructs the analytic signal:
In-Phase (I) : The normalized oscillator value itself
Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation)
This creates a 2D representation: (I, Q). The phase is extracted as:
φ = atan2(Q, I) × (180 / π)
This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through."
The amplitude is extracted as:
A = √(I² + Q²)
This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state).
3. Coherence Calculation Pipeline
For each bar (or every Nth bar if phase sample rate > 1 for performance):
Step 1 : Extract phase φₙ for each of the N active oscillators
Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180)
Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ)
Step 4 : Calculate magnitude: |R| = √
Step 5 : Normalize by count: CI_raw = |R| / N
Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window)
The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability.
The dominant phase is calculated as:
φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π)
This is the angle of the resultant vector R in the complex plane.
4. Entanglement Matrix Construction
For all unique pairs of oscillators (i, j) where i < j:
Step 1 : Get phases φᵢ and φⱼ
Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians)
Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)|
Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j)
The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric.
For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity.
5. Phase-Lock Detection
Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ|
Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ
Step 3 : Find maximum: max_spread = max(Δφ) across all pairs
Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance)
If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter.
6. Signal Generation Logic
Signals are generated through multi-layer confirmation:
Long Ignition Signal :
CI crosses above ignition threshold (e.g., 0.80)
AND dominant phase is in bullish range (-90° < φ_dom < +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold (e.g., 4)
Short Ignition Signal :
CI crosses above ignition threshold
AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold
Collapse Signal :
CI at bar minus CI at current bar > collapse threshold (e.g., 0.55)
AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state)
These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers.
Calculation Methodology
Phase 1: Oscillator Computation and Normalization
On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions:
RSI: ta.rsi(close, length)
MACD: ta.macd() returning histogram component
Stochastic: ta.stoch() smoothed with ta.sma()
CCI: ta.cci(close, length)
Williams %R: ta.wpr(length)
MFI: ta.mfi(hlc3, length)
ROC: ta.roc(close, length)
TSI: ta.tsi(close, short, long)
Each raw value is then passed through a normalization function:
normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1
This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish.
For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to .
Phase 2: Phasor Extraction
For each normalized oscillator value val:
I = val (in-phase component)
Q = val - val (quadrature component, first difference)
Phase calculation:
phi_rad = atan2(Q, I)
phi_deg = phi_rad × (180 / π)
Amplitude calculation:
A = √(I² + Q²)
These values are stored in arrays: osc_phases and osc_amps for each oscillator n.
Phase 3: Complex Summation and Coherence
Initialize accumulators:
sum_cos = 0
sum_sin = 0
For each oscillator n = 0 to N-1:
phi_rad = osc_phases × (π / 180)
sum_cos += cos(phi_rad)
sum_sin += sin(phi_rad)
Resultant magnitude:
resultant_mag = √(sum_cos² + sum_sin²)
Coherence Index (raw):
CI_raw = resultant_mag / N
Smoothed CI:
CI = SMA(CI_raw, smoothing_window)
Dominant phase:
phi_dom_rad = atan2(sum_sin, sum_cos)
phi_dom_deg = phi_dom_rad × (180 / π)
Phase 4: Entanglement Matrix Population
For i = 0 to N-2:
For j = i+1 to N-1:
phi_i = osc_phases × (π / 180)
phi_j = osc_phases × (π / 180)
delta_phi = phi_i - phi_j
E = |cos(delta_phi)|
matrix_index_ij = i × N + j
matrix_index_ji = j × N + i
entangle_matrix = E
entangle_matrix = E
if E >= threshold:
entangled_pairs += 1
The matrix uses flat array storage with index mapping: index(row, col) = row × N + col.
Phase 5: Phase-Lock Check
max_spread = 0
For i = 0 to N-2:
For j = i+1 to N-1:
delta = |osc_phases - osc_phases |
if delta > 180:
delta = 360 - delta
max_spread = max(max_spread, delta)
phase_locked = (max_spread < tolerance)
Phase 6: Signal Evaluation
Ignition Long :
ignition_long = (CI crosses above threshold) AND
(phi_dom > -90 AND phi_dom < 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Ignition Short :
ignition_short = (CI crosses above threshold) AND
(phi_dom < -90 OR phi_dom > 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Collapse :
CI_prev = CI
collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6)
All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true.
Phase 7: Field Strength and Visualization Metrics
Average Amplitude :
avg_amp = (Σ osc_amps ) / N
Field Strength :
field_strength = CI × avg_amp
Collapse Risk (for dashboard):
collapse_risk = (CI - CI) / max(CI , 0.1)
collapse_risk_pct = clamp(collapse_risk × 100, 0, 100)
Quantum State Classification :
if (CI > threshold AND phase_locked):
state = "Ignition"
else if (CI > 0.6):
state = "Coherent"
else if (collapse):
state = "Collapse"
else:
state = "Chaos"
Phase 8: Visual Rendering
Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement:
radius = amplitude × grid_center × 0.8
x = radius × cos(phase × π/180)
y = radius × sin(phase × π/180)
col = center + x (mapped to grid coordinates)
row = center - y
Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient.
Entanglement Web : Render matrix as table cell with background color opacity = E(i,j).
Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI).
All visual components render only on the last bar (barstate.islast) to minimize computational overhead.
How to Use This Indicator
Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction.
Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools.
Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot.
Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence.
Understanding the Circular Orbit Plot
The orbit plot is a polar grid showing oscillator vectors in real-time:
Center point : Neutral (zero phase and amplitude)
Each vector : A line from center to a point on the grid
Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south)
Vector length : The oscillator's amplitude (short = weak signal, long = strong signal)
Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.)
What to watch :
Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning.
Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime.
Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends.
Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals.
Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold.
Reading Dashboard Metrics
The dashboard provides numerical confirmation of what the orbit plot shows visually:
CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries).
Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral.
Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment.
Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals.
Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide).
State : Real-time classification:
🚀 IGNITION: CI just crossed threshold with phase-lock
⚡ COHERENT: CI is high and stable
💥 COLLAPSE: CI has dropped sharply
🌀 CHAOS: Low CI, scattered phases
Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown.
Interpreting Signals
Long Ignition (Blue Triangle Below Price) :
Occurs when CI crosses above threshold (e.g., 0.80)
Dominant phase is in bullish range (-90° to +90°)
All oscillators are phase-locked (within tolerance)
Minimum entangled pairs requirement met
Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw.
Short Ignition (Red Triangle Above Price) :
Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°)
Interpretation : Coherent bearish alignment has formed. High-probability short entry.
Collapse (Circles Above and Below Price) :
CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window
CI was previously above 0.6 (collapsing from coherent state)
Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning.
Phase-Time Heat Map Patterns
Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left).
Pattern: Horizontal Color Bands
If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime.
Pattern: Vertical Color Bands
If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots.
Pattern: Rainbow Chaos
If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation.
Pattern: Color Transition
If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway.
Entanglement Web Analysis
Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators.
Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well.
Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature.
Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself.
How to use :
Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal).
Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation).
Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals.
Trading Workflow
Step 1: Monitor Coherence Level
Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait.
Step 2: Detect Coherence Building
When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare.
Step 3: Confirm Phase Direction
Check the dominant phase angle and the orbit plot quadrant where clustering is occurring:
Clustering in right half (0° to ±90°): Bullish bias forming
Clustering in left half (±90° to 180°): Bearish bias forming
Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇).
Step 4: Wait for Signal Confirmation
Do not enter based on rising CI alone. Wait for the full ignition signal:
CI crosses above threshold
Phase-lock indicator shows 🔒 YES
Entangled pairs count >= minimum
Directional triangle appears on chart
This ensures all layers have aligned.
Step 5: Execute Entry
Long : Blue triangle below price appears → enter long
Short : Red triangle above price appears → enter short
Step 6: Position Management
Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer).
Monitoring :
Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact.
Check dashboard collapse risk. If it rises above 50%, prepare for exit.
Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking.
Exit Triggers :
Collapse signal fires (circles appear)
Dominant phase flips to opposite half-plane
CI drops below 40% (coherence lost)
Price hits your profit target or trailing stop
Step 7: Post-Exit Analysis
After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside.
Best Practices
Use Price Structure as Context
QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example:
Long ignition near a major support level after a pullback: high-probability bounce
Long ignition in the middle of a range with no structure: lower probability
Multi-Timeframe Confirmation
Open QRFM on two timeframes simultaneously:
Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime.
Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias.
This prevents counter-trend trades and increases win rate.
Distinguish Between Regime Types
High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings.
Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish.
Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside.
Adjust Parameters to Instrument and Timeframe
Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10).
Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14).
Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness.
Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction.
Use Entanglement Count as Conviction Filter
The minimum entangled pairs setting controls signal strictness:
Low (1-2) : More signals, lower quality (acceptable if you have other confirmation)
Medium (3-5) : Balanced (recommended for most traders)
High (6+) : Very strict, fewer signals, highest quality
Adjust based on your trade frequency preference and risk tolerance.
Monitor Oscillator Contribution
Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example:
On low-volume instruments, MFI may be unreliable → disable MFI
On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable
Respect the Collapse Signal
Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice:
If in profit: Take partial or full profit on collapse
If at breakeven/small loss: Exit immediately
If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown
Collapses do not guarantee immediate reversals—they signal uncertainty .
Combine with Volume Analysis
If your instrument has reliable volume:
Ignitions with expanding volume: Higher conviction
Ignitions with declining volume: Weaker, possibly false
Collapses with volume spikes: Strong reversal signal
Collapses with low volume: May just be consolidation
Volume is not built into QRFM (except via MFI), so add it as external confirmation.
Observe the Phase Spiral
The spiral provides a quick visual cue for rotation consistency:
Tight, smooth spiral : Ensemble is rotating coherently (trending)
Loose, erratic spiral : Phase is jumping around (ranging or transitional)
If the spiral tightens, coherence is building. If it loosens, coherence is dissolving.
Do Not Overtrade Low-Coherence Periods
When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times:
Reduce position size
Widen stops
Wait for coherence to return
QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside."
Use Alerts Strategically
Set alerts for:
Long Ignition
Short Ignition
Collapse
Phase Lock (optional)
Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify:
Orbit plot shows clustering
Dashboard confirms all conditions
Price structure supports the trade
Do not blindly trade alerts—use them as prompts for analysis.
Ideal Market Conditions
Best Performance
Instruments :
Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto)
Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets)
Timeframes :
15-minute to 4-hour: Optimal balance of noise reduction and responsiveness
1-hour to daily: Slower, higher-conviction signals; good for swing trading
5-minute: Acceptable for scalping if parameters are tightened and you accept more noise
Market Regimes :
Trending markets with periodic retracements (where oscillators cycle through phases predictably)
Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion)
Rotational markets with clear swings (oscillators phase-lock at turning points)
Volatility :
Moderate to high volatility (oscillators have room to move through their ranges)
Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses)
Challenging Conditions
Instruments :
Very low liquidity markets (erratic price action creates unstable oscillator phases)
Heavily news-driven instruments (fundamentals may override technical coherence)
Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence)
Market Regimes :
Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire)
Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes)
Gap-driven markets (large overnight gaps create phase discontinuities)
Timeframes :
Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable
Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading
Special Cases :
During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside.
In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through.
Adaptive Behavior
QRFM is designed to self-adapt to poor conditions:
When coherence is genuinely absent, CI remains low and signals do not fire
When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out
When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals
This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades.
Parameter Optimization by Trading Style
Scalping (5-15 Minute Charts)
Goal : Maximum responsiveness, accept higher noise
Oscillator Lengths :
RSI: 7-10
MACD: 8/17/6
Stochastic: 8-10, smooth 2-3
CCI: 14-16
Others: 8-12
Coherence Settings :
CI Smoothing Window: 2-3 bars (fast reaction)
Phase Sample Rate: 1 (every bar)
Ignition Threshold: 0.65-0.75 (lower for more signals)
Collapse Threshold: 0.40-0.50 (earlier exit warnings)
Confirmation :
Phase Lock Tolerance: 40-50° (looser, easier to achieve)
Min Entangled Pairs: 2-3 (fewer oscillators required)
Visuals :
Orbit Plot + Dashboard only (reduce screen clutter for fast decisions)
Disable heavy visuals (heat map, web) for performance
Alerts :
Enable all ignition and collapse alerts
Set to "Once per bar close"
Day Trading (15-Minute to 1-Hour Charts)
Goal : Balance between responsiveness and reliability
Oscillator Lengths :
RSI: 14 (standard)
MACD: 12/26/9 (standard)
Stochastic: 14, smooth 3
CCI: 20
Others: 10-14
Coherence Settings :
CI Smoothing Window: 3-5 bars (balanced)
Phase Sample Rate: 2-3
Ignition Threshold: 0.75-0.85 (moderate selectivity)
Collapse Threshold: 0.50-0.55 (balanced exit timing)
Confirmation :
Phase Lock Tolerance: 30-40° (moderate tightness)
Min Entangled Pairs: 4-5 (reasonable confirmation)
Visuals :
Orbit Plot + Dashboard + Heat Map or Web (choose one)
Field Cloud for regime backdrop
Alerts :
Ignition and collapse alerts
Optional phase-lock alert for advance warning
Swing Trading (4-Hour to Daily Charts)
Goal : High-conviction signals, minimal noise, fewer trades
Oscillator Lengths :
RSI: 14-21
MACD: 12/26/9 or 19/39/9 (longer variant)
Stochastic: 14-21, smooth 3-5
CCI: 20-30
Others: 14-20
Coherence Settings :
CI Smoothing Window: 5-10 bars (very smooth)
Phase Sample Rate: 3-5
Ignition Threshold: 0.80-0.90 (high bar for entry)
Collapse Threshold: 0.55-0.65 (only significant breakdowns)
Confirmation :
Phase Lock Tolerance: 20-30° (tight clustering required)
Min Entangled Pairs: 5-7 (strong confirmation)
Visuals :
All modules enabled (you have time to analyze)
Heat Map for multi-bar pattern recognition
Web for deep confirmation analysis
Alerts :
Ignition and collapse
Review manually before entering (no rush)
Position/Long-Term Trading (Daily to Weekly Charts)
Goal : Rare, very high-conviction regime shifts
Oscillator Lengths :
RSI: 21-30
MACD: 19/39/9 or 26/52/12
Stochastic: 21, smooth 5
CCI: 30-50
Others: 20-30
Coherence Settings :
CI Smoothing Window: 10-14 bars
Phase Sample Rate: 5 (every 5th bar to reduce computation)
Ignition Threshold: 0.85-0.95 (only extreme alignment)
Collapse Threshold: 0.60-0.70 (major regime breaks only)
Confirmation :
Phase Lock Tolerance: 15-25° (very tight)
Min Entangled Pairs: 6+ (broad consensus required)
Visuals :
Dashboard + Orbit Plot for quick checks
Heat Map to study historical coherence patterns
Web to verify deep entanglement
Alerts :
Ignition only (collapses are less critical on long timeframes)
Manual review with fundamental analysis overlay
Performance Optimization (Low-End Systems)
If you experience lag or slow rendering:
Reduce Visual Load :
Orbit Grid Size: 8-10 (instead of 12+)
Heat Map Time Bins: 5-8 (instead of 10+)
Disable Web Matrix entirely if not needed
Disable Field Cloud and Phase Spiral
Reduce Calculation Frequency :
Phase Sample Rate: 5-10 (calculate every 5-10 bars)
Max History Depth: 100-200 (instead of 500+)
Disable Unused Oscillators :
If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops.
Simplify Dashboard :
Choose "Small" dashboard size
Reduce number of metrics displayed
These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness.
Important Disclaimers
This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty.
No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics.
Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades.
Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries.
Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside.
Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose.
Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital.
No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes.
Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness.
This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning.
Technical Notes
Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation.
Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary.
Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed).
Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically.
Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations.
Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise.
Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)).
Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared).
Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals.
Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross).
Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red).
No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests.
Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies.
— Dskyz, Engineering precision. Trading coherence.
Pre-London & London Session (Auto DST) MMMThis indicator automatically marks the Pre-London and London Open sessions for any trading day, with full U.S. Daylight Saving Time (DST) adjustment.
It’s ideal for traders backtesting Gold (XAUUSD) or other pairs sensitive to London liquidity, as it dynamically shifts between UTC-4 and UTC-5 to stay perfectly aligned with institutional session timing.
Features:
🕑 Auto-detects whether the date falls under U.S. Daylight or Standard Time
🟧 Highlights Pre-London session (2 a.m.–3 a.m. EDT / 1 a.m.–2 a.m. EST)
🟩 Highlights London session (3 a.m.–5 a.m. EDT / 2 a.m.–4 a.m. EST)
⚙️ No manual adjustments needed — fully automatic for any backtest date
📈 Perfect for ICT, Smart Money, and liquidity-based session strategies
Recommended settings:
Chart timezone: New York
Works on all symbols and timeframes
XAUUSD 5m — NY Supertrend+RSI Optimizer (1:2 RR) — $240k/orderThis strategy is built for XAUUSD (Gold) on the 5-minute timeframe, focusing exclusively on the New York trading session (08:00–17:00 NY time) — the most volatile and liquid hours of the day.
It combines a Supertrend trend filter with RSI momentum signals to identify high-probability entries, using a 1:2 risk–reward ratio for disciplined trade management.
🧠 Strategy Logic:
Buy Condition: RSI crosses above 55 while Supertrend indicates an uptrend
Sell Condition: RSI crosses below 45 while Supertrend indicates a downtrend
Session Filter: Trades only between 08:00 → 17:00 New York time
Risk/Reward: 1:2 (Take-Profit = 2× Stop-Loss distance from Supertrend line)
Position Size: $240,000 notional per order
Auto-Exit: Closes all trades at NY session end
⚡ Highlights:
Targets NY session volatility
Combines trend + momentum for cleaner entries
Strict 1:2 RR for consistent outcomes
Avoids overnight exposure
⚠️ Disclaimer:
This script is intended for educational and research purposes only.
Past performance is not indicative of future results.
Always forward-test on demo before using live capital.
XAUUSD 5m — CET 13:00→01:00 Supertrend + RSI (1:2 RR) — $240KThis strategy is designed for XAUUSD (Gold) on the 5-minute chart, optimized for trading during the most active hours (13:00–01:00 CET).
It combines a Supertrend direction filter with RSI crossovers for precise entries, and applies a 1:2 risk–reward ratio for consistent risk management.
🧠 Logic Overview:
Buy Signal: RSI crosses above 55 while Supertrend is bullish
Sell Signal: RSI crosses below 45 while Supertrend is bearish
Trading Hours: 13:00 → 01:00 CET (corresponding to 07:00 → 19:00 New York time)
Risk Management: Fixed 1:2 RR (TP = 2× SL distance from Supertrend line)
Session Management: Automatically closes all trades after 01:00 CET
Order Size: $240,000 notional exposure per position
💡 Best used for:
Scalping or intraday trading on XAUUSD during high-volatility hours.
The setup works best when combined with strong price action or volume confirmation.
⚠️ Disclaimer:
This script is for educational and testing purposes only.
Past performance does not guarantee future results.
Always test on demo before using live funds.
Sultan_Mstrading Dynamic Levels (Auto-Market Final Version)The Sultan_Mstrading Dynamic Levels indicator automatically generates dynamic support and resistance levels based on the market type or trading symbol (such as Gold, Bitcoin, Indices, Oil, or Forex pairs).
It plots multiple levels above and below the current price with adjustable spacing, and automatically highlights the nearest level to the current price for quick visual reference
5-Year Returns Chart BTCvsSPXvsGOLDvsNVDACompare between thes 4 assets:
BTC
NVDA
SPX
GOLD
With an initial 1000$ investment in the last 5 years each return
FluxVector Liquidity Universal Trendline FluxVector Liquidity Trendline FFTL
Summary in one paragraph
FFTL is a single adaptive trendline for stocks ETFs FX crypto and indices on one minute to daily. It fires only when price action pressure and volatility curvature align. It is original because it fuses a directional liquidity pulse from candle geometry and normalized volume with realized volatility curvature and an impact efficiency term to modulate a Kalman like state without ATR VWAP or moving averages. Add it to a clean chart and use the colored line plus alerts. Shapes can move while a bar is open and settle on close. For conservative alerts select on bar close.
Scope and intent
• Markets. Major FX pairs index futures large cap equities liquid crypto top ETFs
• Timeframes. One minute to daily
• Default demo used in the publication. SPY on 30min
• Purpose. Reduce false flips and chop by gating the line reaction to noise and by using a one bar projection
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. Directional Liquidity Pulse plus Volatility Curvature plus Impact Efficiency drives an adaptive gain for a one dimensional state
• Failure mode addressed. One or two shock candles that break ordinary trendlines and saw chop in flat regimes
• Testability. All windows and gains are inputs
• Portable yardstick. Returns use natural log units and range is bar high minus low
• Protected scripts. Not used. Method disclosed plainly here
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close. Average absolute return over a window is a unit of motion
Components
• Directional Liquidity Pulse DLP. Measures signed participation from body and wick imbalance scaled by normalized volume and variance stabilized
• Volatility Curvature. Second difference of realized volatility from returns highlights expansion or compression
• Impact Efficiency. Price change per unit range and volume boosts gain during efficient moves
• Energy score. Z scores of the above form a single energy that controls the state gain
• One bar projection. Current slope extended by one bar for anticipatory checks
Fusion rule
Weighted sum inside the energy score then logistic mapping to a gain between k min and k max. The state updates toward price plus a small flow push.
Signal rule
• Long suggestion and order when close is below trend and the one bar projection is above the trend
• Short suggestion and flip when close is above trend and the one bar projection is below the trend
• WAIT is implicit when neither condition holds
• In position states end on the opposite condition
What you will see on the chart
• Colored trendline teal for rising red for falling gray for flat
• Optional projection line one bar ahead
• Optional background can be enabled in code
• Alerts on price cross and on slope flips
Inputs with guidance
Setup
• Price source. Close by default
Logic
• Flow window. Typical range 20 to 80. Higher smooths the pulse and reduces flips
• Vol window. Typical range 30 to 120. Higher calms curvature
• Energy window. Typical range 20 to 80. Higher slows regime changes
• Min gain and Max gain. Raise max to react faster. Raise min to keep momentum in chop
UI
• Show 1 bar projection. Colors for up down flat
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• Commission percent 0.03
• Slippage 5
• Default order size method percent of equity value 3%
• Pyramiding 0
• Process orders on close off
• Calc on every tick off
• Recalculate after order is filled off
Realism and responsible publication
• No performance claims
• Intrabar reminder. Shapes can move while a bar forms and settle on close
• Strategy uses standard candles only
Honest limitations and failure modes
• Sudden gaps and thin liquidity can still produce fast flips
• Very quiet regimes reduce contrast. Use larger windows and lower max gain
• Session time uses the exchange time of the chart if you enable any windows later
• Past results never guarantee future outcomes
Open source reuse and credits
• None
NOVA Breakout Signals v2.2 (TF M30)A clean, rules-based breakout signal tool for 30-minute charts.
It detects Dow swing breakouts and filters them with RSI, MACD and Volume so you only see the higher-quality entries. The script does not place trades and does not calculate SL/TP – it only prints clear LONG/SHORT labels at the entry price.
⸻
How it works
1. Timeframe enforcement – Signals are generated only on M30. On other timeframes the script shows a notice and stays silent.
2. Breakout engine (Dow swings) – The last confirmed swing high/low (pivots) is tracked.
• Breakout Up: bar closes above the last swing high by a small buffer.
• Breakout Down: bar closes below the last swing low by a small buffer.
3. Quality filters (all must be true):
• RSI (default length 30):
• Long: RSI > threshold and rising.
• Short: RSI < threshold and falling.
• MACD (12/26/9):
• Long: histogram > 0 and line > signal.
• Short: histogram < 0 and line < signal.
• Volume: current volume > SMA(volume, 20) × multiplier.
4. Debounce / anti-spam
• Cooldown of 4 hours (8 M30 bars) after any signal.
• Minimum price distance from the previous signal to avoid clustered labels.
Signals appear once the bar closes (barstate.isconfirmed). No swing lines are drawn to keep the chart clean; only entry labels are shown.
⸻
Inputs (key)
• RSI length & thresholds for Long/Short confirmation.
• MACD uses 12/26/9 (fixed).
• Volume multiplier (relative to SMA 20).
• Breakout buffer %, Cooldown hours, Min distance %.
• Show labels (on/off).
⸻
Usage tips
• Start with gold/major FX/indices on M30; use “Once per bar close” if you attach alerts.
• Increase the breakout buffer and volume multiplier in choppy markets.
• Tighten RSI thresholds (e.g., 55/45) if you want fewer but stronger signals.
⸻
Notes & limitations
• Pivots confirm after a few bars by definition; signals themselves are printed only on confirmed bar close and do not repaint once shown.
• This is a signal indicator, not investment advice. Always manage risk.
Relative Valuation OscillatorThis is a Relative Valuation Oscillator (RVO) this is attempt of replication OTC Valuation - a sophisticated multi-asset comparison indicator designed to measure whether the current asset is overvalued or undervalued relative to up to three reference assets.
Overview
The RVO compares the current chart's asset against reference assets (default: 30-Year Treasury Bonds, Gold, and US Dollar Index) to determine relative strength and valuation extremes. It outputs normalized oscillator values ranging from -100 (undervalued) to +100 (overvalued).
Key Features
Multiple Calculation Methods
The indicator offers 5 different calculation approaches:
Simple Ratio - Normalized ratio deviation from average
Percentage Difference - Percentage change comparison
Ratio Z-Score - Standard deviation-based comparison
Rate of Change Comparison - Momentum differential analysis (default)
Normalized Ratio - Min-max normalized ratio
Configurable Reference Assets
Asset 1: Default ZB (30-Year Treasury Bond Futures) - tracks interest rate sensitivity
Asset 2: Default GC (Gold Futures) - tracks safe-haven and inflation dynamics
Asset 3: Default DXY (US Dollar Index) - tracks currency strength
Each asset can be enabled/disabled independently
Fully customizable symbols
Visual Components
Multiple oscillator lines - One for each active reference asset (color-coded)
Average line - Combined signal from all active assets
Overbought/Oversold zones - Configurable threshold levels (default: ±80)
Zero line - Neutral valuation reference
Background coloring - Visual zones for extreme conditions
Signal line - Optional smoothed average
Entry markers - Long/short signals at key reversals
Signal Generation
Crossover alerts - When crossing overbought/oversold levels
Entry signals - Reversals from extreme zones
Divergence detection - Bullish/bearish divergences between price and oscillator
Zero-line crosses - Trend strength changes
Customization Options
Lookback period (10-500): Controls statistical calculation window
Normalization period (50-1000): Determines scaling sensitivity
Smoothing toggle: Optional EMA/SMA smoothing with adjustable period
Visual customization: Colors, levels, and display options
Information Table
Real-time dashboard showing:
Average oscillator value
Current status (Overvalued/Undervalued/Neutral)
Current asset price
Individual values for each active reference asset
Use Cases
Mean reversion trading - Identify extreme relative valuations for reversal trades
Sector rotation - Compare assets within similar categories
Hedging strategies - Understand correlation dynamics
Multi-asset analysis - Simultaneously compare against bonds, commodities, and currencies
Divergence trading - Spot price/oscillator divergences
Trading Strategy Applications
Long signals: When oscillator crosses above oversold level (asset recovering from undervaluation)
Short signals: When oscillator crosses below overbought level (asset declining from overvaluation)
Confirmation: Use multiple reference assets for stronger signals
Risk management: Avoid trading when all assets show neutral readings
This indicator is particularly useful for traders who want to incorporate inter-market analysis and relative strength concepts into their trading decisions, especially in OTC (Over-The-Counter) and futures markets.
