S&P Power Hour Liquidity Sweep StrategyThis indicator is designed for intraday traders who want to take advantage of liquidity grabs, break of structure (BOS), and optimal entry points during the most volatile hours of the trading day: the NYSE Power Hours (09:30–10:30 AM and 02:30–04:00 PM EST).
Key Features:
Power Hour Detection:
Automatically identifies the two most liquid hours of the trading session.
Liquidity Sweep Detection:
Highlights when price sweeps a recent swing high or low — a common trap before reversals.
Break of Structure (BOS):
Confirms trend shift after a liquidity sweep with smart money-style BOS markers.
Fair Value Gap (FVG) Highlighting: (Optional)
Spot institutional imbalances between candles to fine-tune trade entries.
How It Works:
Wait for price to sweep a swing high or low during the power hours.
Look for a break of structure (BOS) in the opposite direction.
Enter on the next candle or FVG retest.
The indicator will plot a yellow circle for entry, a red line for stop, and a green line for the target (based on your RR setting).
Customizable Inputs:
Swing sensitivity (lookback bars)
Risk-to-reward ratio
Optional FVG visibility
Best Used With:
Higher timeframe bias (15m/1H)
Order blocks or volume analysis
Avoiding major news events
Whether you're a scalper or precision-based intraday trader, this tool helps you spot high-probability reversal setups with clean visuals and clear confirmations.
Indicatori e strategie
MTF RSI MA System + Adaptive BandsMTF RSI MA System + Adaptive Bands
Overview
MTF RSI MA System + Adaptive Bands is a highly customizable Pine Script indicator for traders seeking a versatile tool for multi-timeframe (MTF) analysis. Unlike traditional RSI, it focuses on the Moving Average of RSI (RSI MA), delivering smoother and more flexible trading signals. The main screenshot displays the indicator in two panels to showcase its diverse capabilities.
Important: Timeframes do not adjust automatically – users must manually set them to match the chart’s timeframe.
Features
Core Component: Built around RSI MA, not raw RSI, for smoother trend signals.
Multi-Timeframe: Analyze RSI MA across three customizable timeframes (default: 4H, 8H, 12H).
Adaptive Bands: Three band calculation methods (Fixed, Percent, StdDev) for dynamic signals.
Flexible Signals: Generated via RSI MA crossovers, band interactions, or directional alignment across timeframes.
Background Coloring: Highlights when RSI MAs across timeframes move in the same direction, aiding trend confirmation.
Screenshot Panels Configuration
Upper Panel: Shows RSI, RSI MA, and fixed bands for reversal strategies (RSI crossing bands).
Lower Panel: Displays three RSI MAs (Alligator-style) for trend-following, with background coloring for directional alignment.
Band Calculation Methods
The indicator offers three ways to calculate bands around RSI MA, each with unique characteristics:
Fixed Bands
Set at a fixed point value (default: 10) above and below RSI MA.
Example: If RSI MA = 50, band value = 10 → upper band = 60, lower = 40.
Use Case: Best for stable markets or fixed-range preferences.
Tip: Adjust the band value to widen or narrow the range based on asset volatility.
Percent Bands
Calculated as a percentage of RSI MA (default: 10%).
Example: If RSI MA = 50, band value = 10% → upper band = 55, lower = 45.
Use Case: Ideal for assets with varying volatility, as bands scale with RSI MA.
Tip: Experiment with percentage values to match typical price swings.
Standard Deviation Bands (StdDev)
Based on RSI’s standard deviation over the MA period, multiplied by a user-defined factor (default: 10).
Example: If RSI MA = 50, standard deviation = 5, factor = 2 → upper band = 60, lower = 40.
Important: The default value (10) may produce wide bands. Reduce to 1–2 for tighter, practical bands.
Use Case: Best for dynamic markets with fluctuating volatility.
Configuration Options
RSI Length: Set RSI calculation period (default: 20).
MA Length: Set RSI MA period (default: 20).
MA Type: Choose SMA or EMA for RSI MA (default: EMA).
Timeframes: Configure three timeframes (default: 4H, 8H, 12H) for MTF analysis.
Overbought/Oversold Levels: Optionally display fixed levels (default: 70/30).
Background Coloring: Enable/disable for each timeframe to highlight directional alignment.
How to Use
Add Indicator: Load it onto your TradingView chart.
Setup:
Reversals: Configure like the upper panel (RSI, RSI MA, bands) and watch for RSI crossing bands.
Trends: Configure like the lower panel (three RSI MAs) and look for fastest MA crossovers and background coloring.
Adjust Timeframes: Manually set tf1, tf2, tf3 (e.g., 1H, 2H, 4H on a 1H chart) to suit your strategy.
Adjust Bands: Choose band type (Fixed, Percent, StdDev) and value. For StdDev, reduce to 1–2 for tighter bands.
Experiment: Test settings to match your trading style, whether scalping, swing trading, or long-term.
Notes
Timeframes: Always match tf1, tf2, tf3 to your chart’s needs, as they don’t auto-adjust.
StdDev Bands: Lower the default value (10) to avoid overly wide bands.
Versatility: Works across markets (stocks, forex, crypto).
Market Matrix ViewThis technical indicator is designed to provide traders with a quick and integrated view of market dynamics by combining several popular indicators into a single tool. It's not a magic bullet, but a practical aid for analyzing buying/selling pressure, trends, volume, and divergences, saving you time in the decision-making process. Built for flexibility, the indicator adapts to various trading styles (scalping, swing, or long-term) and offers customizable settings to suit your needs.
🟡 Multi-Timeframe Trends
➤ This section displays the trend direction (bullish, bearish, or neutral) across 15-minute, 1-hour, 4-hour, and Daily timeframes, providing multi-timeframe market context. Timeframes lower than the one currently selected will show "N/A."
➤It utilizes fast and slow Exponential Moving Averages (EMAs) for each timeframe:
15m: Fast EMA 42, Slow EMA 170
1h: Fast EMA 40, Slow EMA 100
4h: Fast EMA 36, Slow EMA 107
Daily: Fast EMA 20, Slow EMA 60
🟡 Smart Flow & RVOL
➤ This section displays "Buying Pressure" or "Selling Pressure" signals based on indicator confluence, alongside volume activity ("High Activity," "Normal Activity," or "Low Activity").
➤ Smart Flow combines Chaikin Money Flow (CMF) and Money Flow Index (MFI) to detect buying/selling pressure. CMF measures money flow based on price position within the high-low range, while MFI analyzes money flow considering typical price and volume. A signal is generated only when both indicators simultaneously increase/decrease beyond an adjustable threshold ("Buy/Sell Sensitivity") and volume exceeds a Simple Moving Average (SMA) scaled by the "Volume Multiplier."
➤ RVOL (Relative Volume) calculates relative volume separately for bullish and bearish candles, comparing recent volume (fast SMA) with a reference volume (slow SMA). Thresholds are adjusted based on the selected mode.
🟡 ADX & RSI
This section displays trend strength ("Strong," "Moderate," or "Weak"), its direction ("Bullish" or "Bearish"), and the RSI momentum status ("Overbought," "Oversold," "Buy/Sell Momentum," or "Neutral").
➤ ADX (Average Directional Index) measures trend strength (above 40 = "Strong," 20–40 = "Moderate," below 20 = "Weak"). Direction is determined by comparing +DI (upward movement) with -DI (downward movement). Additionally, an arrow indicates whether the trend's strength is decreasing or increasing.
➤RSI (Relative Strength Index) evaluates price momentum. Extreme levels (above 80/85 = "Overbought," below 15/20 = "Oversold") and intermediate zones (47–53 = "Neutral," above 53 = "Buy Momentum," below 47 = "Sell Momentum") are adjusted based on the selected mode.
🟡 When these signals are active for a potential trade setup, the table's background lights up green or red, respectively.
🟡 Volume Spikes
➤This feature highlights bars with significantly higher volume than the recent average, coloring them yellow on the chart to draw attention to intense market activity.
➤It uses the Z-Score method to detect volume anomalies. Current volume is compared to a 10-bar Simple Moving Average (SMA) and the standard deviation of volume over the same period. If the Z-Score exceeds a certain threshold, the bar is marked as a volume spike.
🟡 Divergences (Volume Divergence Detection)
➤ This feature marks divergences between price and technical indicators on the chart, using diamond-shaped labels (green for bullish divergences, red for bearish divergences) to signal potential trend reversals.
➤ It compares price deviations from a Simple Moving Average (SMA) with deviations of three indicators: Chaikin Money Flow (CMF), Money Flow Index (MFI), and On-Balance Volume (OBV). A bullish divergence occurs when price falls below its average, but CMF, MFI, and OBV rise above their averages, indicating hidden accumulation. A bearish divergence occurs when price rises above its average, but CMF, MFI, and OBV fall, suggesting distribution. The length of the moving averages is adjustable (default 13/10/5 bars for Scalping/Balanced/Swing), and detection thresholds are scaled by "Divergence Sensitivity" (default 1.0).
🟡 Adaptive Stop-Loss (ATR)
➤Draws dynamic stop-loss lines (red, dashed) on the chart for buy or sell signals, helping traders manage risk.Uses the Average True Range (ATR) to calculate stop-loss levels, set at low/high ± ATR × multiplier
🟡 Alerts for trend direction changes in the Info Panel:
➤ Triggers notifications when the trend shifts to Bullish (when +DI crosses above -DI) or Bearish (when +DI crosses below -DI), helping you stay informed about key market shifts.
How to use: Set alerts in Trading View for “Trend Changed to Bullish” or “Trend Changed to Bearish” with “Once Per Bar Close” for reliable signals.
🟡 Settings (Inputs)
➤ The indicator offers customizable settings to fit your trading style, but it's already optimized for Scalping (1m–15m), Balanced (16m–3h59m), and Swing (4h–Daily) modes, which automatically adjust based on the selected timeframe. The visible inputs allow you to adjust the following parameters:
Show Info Panel: Enables/disables the information panel (default: enabled).
Show Volume Spikes: Turns on/off coloring for volume spike bars (default: enabled).
Spike Sensitivity: Controls the Z-Score threshold for detecting volume spikes (default: 2.0; lower values increase signal frequency).
Show Divergence: Enables/disables the display of divergence labels (default: enabled).
Divergence Sensitivity: Adjusts the thresholds for divergence detection (default: 1.0; higher values reduce sensitivity).
Divergence Lookback Length: Sets the length of the moving averages used for divergences (default: 5, automatically adjusted to 13/10/5 for Scalping/Balanced/Swing).
RVOL Reference Period: Defines the reference period for relative volume (default: 20, automatically adjusted to 7/15/20).
RSI Length: Sets the RSI length (default: 14, automatically adjusted to 5/10/14).
Buy Sensitivity: Controls the increase threshold for Buying Pressure signals (default: 0.007; higher values reduce frequency).
Sell Sensitivity: Controls the decrease threshold for Selling Pressure signals (default: 0.007; higher values reduce frequency).
Volume Multiplier (B/S Pressure): Adjusts the volume threshold for Smart Flow signals (default: 0.6; higher values require greater volume).
🟡 This indicator is created to simplify market analysis, but I am not a professional in Pine Script or technical indicators. This indicator is not a standalone solution. For optimal results, it must be integrated into a well-defined trading strategy that includes risk management and other confirmations.
IU Market Rhythm WaveDESCRIPTION:
The IU Market Rhythm Wave is a multi-dimensional indicator designed to reveal the underlying rhythm and energy of the market. By analyzing price momentum, harmonic oscillations, volume behavior, and market breadth, it helps traders identify high-quality long and short wave signals. It also visualizes rhythm bands, wave strength zones, and harmonic levels to provide comprehensive context for decision-making.
This tool is best used on trending instruments where rhythm cycles and volume patterns create clear wave-based opportunities.
USER INPUTS:
Rhythm Cycle Length
Controls the main lookback period used to calculate price waves, harmonic oscillation, volume rhythm, and breath. A longer cycle smooths signals, while a shorter cycle makes them more responsive. Recommended range: 8 to 35.
Wave Signal Strength
Multiplies the standard deviation of rhythm to define dynamic breakout thresholds. A higher value results in fewer but stronger signals, filtering out minor fluctuations.
Harmonic Filter
Applies a sensitivity filter to the harmonic mean and standard deviation. It helps eliminate weak or noisy signals and ensures rhythm-based signals align with harmonic structure.
Show Wave Energy Zones
Toggles background color shading based on current rhythm conditions. Greenish zones indicate strong upward rhythm, red for strong downward rhythm, yellow for positive bias, and gray for weak or neutral zones.
Show Rhythm Bands
Enables the display of upper and lower rhythm bands derived from ATR and rhythm volatility. These bands act as dynamic price envelopes and potential support/resistance zones.
Wave Zone Opacity
Adjusts the transparency of background energy zones, allowing users to control how prominent these zones appear on the chart. Range: 60 to 90 for optimal visibility.
INDICATOR LOGIC:
The indicator combines multiple rhythmic components into a composite rhythm score:
1. Price Wave – Based on momentum (rate of price change) smoothed by a moving average.
2. Harmonic Oscillation – Measures how far price has deviated from a central harmonic average (HLC3).
3. Volume Rhythm – Uses volume’s deviation from its mean, standardized by its volatility.
4. Market Breath – Captures range expansion and closing strength relative to range.
These elements form the Raw Rhythm, which is further smoothed to produce the Market Rhythm. When the rhythm exceeds statistically calculated thresholds and other conditions like volume confirmation and harmonic proximity are met, wave signals are triggered.
Harmonic Fibonacci levels (0.236, 0.382, 0.618, 0.764) are also calculated every rhythm cycle to identify nearby structural price zones. Signals occurring near these levels are considered more reliable.
The Rhythm Bands use ATR and rhythm strength to define dynamic boundaries above and below price. Visual zones and arrows mark rhythm shifts and highlight the underlying energy of the market.
WHY IT IS UNIQUE:
This indicator goes beyond traditional oscillators or volume indicators by blending multiple market dimensions into one rhythmic framework. It adapts to volatility, applies harmonic structure awareness, and filters signals based on real-time market conditions. It offers:
* A unique rhythm-based view of price, volume, and volatility
* Dynamic, adaptive signal generation and zone coloring
* Visual analytics and contextual data in a summary table
* Signal filtering using harmonic alignment and market breath
Its real-time responsiveness and multi-layered logic make it suitable for intraday, swing, and positional traders.
HOW USER CAN BENEFIT FROM IT:
* Spot high-conviction long or short entries when rhythm, volume, and structure align
* Avoid low-quality trades during weak or noisy rhythm periods
* Use visual wave zones to gauge trend strength and rhythm direction
* Monitor harmonic proximity to enter or exit near key structural levels
* Apply rhythm bands for dynamic stop-loss and target setting
* Use rhythm direction arrows and analytics table to gain deeper market insight
DISCLAIMER:
This indicator is created for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any asset. All trading involves risk, and users should conduct their own analysis or consult with a qualified financial advisor before making any trading decisions. The creator is not responsible for any losses incurred through the use of this tool. Use at your own discretion.
ORB Breakout Indicator - NQ1!The purpose of this indicator is to assist traders in rapidly identifying high-probability Opening Range Breakout (ORB) setups on the NQ1! 1-minute time frame (Nasdaq Futures)
Key Features:
Opening Range: Automatically plots the high and low of the 1st 15min of the (NYSE session) (09:30–09:45 EST)
Breakout Signals : Illustrates the first candle that breaks upward or downward and:
Green arrow for a bullish breakout
Red arrow for a bearish breakout
Clean Visuals: Dynamic lines show the high and low of the ORB window for easy reference.
(DON'T USE THIS ONLY FOR ENTRY SIGNALS, PAIR THIS WITH OTHER INFLUENCES TO GET HIGH PROBABILITY BREAKOUTS)
Luma DCA Simulator (BTC only)Luma DCA Simulator – Guide
What is the Luma DCA Simulator?
The Luma DCA Tracker shows how regular Bitcoin investments (Dollar Cost Averaging) would have developed over a freely selectable period – directly in the chart, transparent and easy to follow.
Settings Overview
1. Investment amount per interval
Specifies how much capital is invested at each purchase (e.g. 100).
2. Start date
Defines the point in time from which the simulation begins – e.g. 01.01.2020.
3. Investment interval
Determines how frequently investments are made:
– Daily
– Weekly
– Every 14 days
– Monthly
4. Language
Switches the info box display between English and German.
5. Show investment data (optional)
If activated, the chart will display additional values such as total invested capital, BTC amount, current value, and profit/loss.
What the Chart Displays
Entry points: Each DCA purchase is marked as a point in the price chart.
Average entry price: An orange line visualizes the evolving DCA average.
Info box (bottom left) with a live summary of:
– Total invested capital
– Total BTC acquired
– Average entry price
– Current portfolio value
– Profit/loss in absolute terms and percentage
Note on Accuracy
This simulation is for illustrative purposes only.
Spreads, slippage, fees, and tax effects are not included.
Actual results may vary.
Technical Note
For daily or weekly intervals, the chart timeframe should be set to 1 day or lower to ensure all purchases are accurately included.
Larger timeframes (e.g. weekly or monthly charts) may result in missed investments.
Currency Handling
All calculations are based on the selected chart symbol (e.g. BTCUSD, BTCEUR, BTCUSDT).
The displayed currency is automatically determined by the chart used.
Top Right Watermark# TopRight Watermark
**Finally, a watermark that stays out of your way!**
Tired of TradingView's default watermark blocking your price action and technical analysis? This customizable watermark indicator gives you complete control over positioning and content display.
## 🎯 Key Features
**✅ Flexible Positioning** - Place anywhere: corners, sides, or edges
**✅ Multi-Slot Display** - Up to 3 customizable information slots
**✅ Individual Font Control** - Different sizes for each slot
**✅ Platform Compatibility** - TradingView OR MetaTrader timeframe formats
**✅ Clean & Professional** - Customizable colors and transparency
## 🔧 What You Can Display
- **Timeframe** - Current chart period
- **Ticker** - Symbol name (smart formatting for crypto/forex)
- **Exchange** - Broker/platform name
- **Custom Text** - Your own message
- **Empty** - Hide unused slots
## 🎨 Customization Options
- **Position**: 9 placement options (top/middle/bottom + left/center/right)
- **Colors**: Full color picker with transparency control
- **Font Sizes**: 5 sizes available per slot (tiny to huge)
- **Timeframe Style**: Choose TradingView (1m, 4H) or MetaTrader (M1, H4) format
## 🚀 Perfect For
- Traders who need clean chart visibility
- Multi-timeframe analysis
- Professional chart screenshots
- Platform migrants (MT4/MT5 to TradingView)
- Anyone wanting organized chart information
## 💡 Pro Tips
- Place in corners to avoid price action interference
- Combine Exchange + Ticker + Timeframe for complete context
- Use transparency to make it subtle but visible
**Stop letting watermarks interfere with your trading analysis. Take control of your chart display today!**
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*Compatible with all TradingView chart types and timeframes. Easy setup with intuitive controls.*
Watermark by HAZEDEnhanced Watermark - Clean Chart Labeling
A professional watermark indicator for traders who want clean, customizable chart identification.
Features:
- Show/hide: Exchange prefix, timeframe, price change %, volume
- 9 positioning options - place anywhere on your chart
- Custom text styling - normal or spaced text modes
- Full color control - including transparency settings
- Size customization - independent sizing for each element
- Personal signature - add your trading brand
- Custom symbols - personalize arrows and indicators
Perfect for:
Content creators, educational posts, professional setups, and social media sharing.
Easy to use: Works immediately with smart defaults. Fully customizable to match your style.
Clean charts, professional presentation.
Adaptive Multi-MA OptimizerAdaptive Multi-MA Optimizer
This indicator provides a powerful, customizable solution for traders seeking dynamically optimized moving averages with precision and control. It integrates multiple custom-built moving average types, applies real-time volatility-based optimization, and includes an optional composite smoothing engine.
🧠 Key Features
Dynamic Optimization:
Automatically selects the optimal lookback length based on market volatility stability using a custom standard deviation differential model.
Multiple Custom MA Types:
Includes fully custom implementations of:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
VWMA (Volume Weighted MA)
DEMA (Double EMA)
TEMA (Triple EMA)
Hull MA
ALMA (Arnaud Legoux MA)
Composite MA Option:
A unique "Composite" mode blends all supported MAs into a single average, then applies optional smoothing for enhanced signal clarity.
Dynamic Smoothing:
The composite mode supports volatility-adjusted smoothing (based on optimized lookback), making it adaptable to different market regimes.
Fully Custom Logic:
No built-in MA functions are used — every moving average is hand-coded for transparency and educational value.
⚙️ How It Works
Optimization:
The script evaluates a range of lengths (minLen to maxLen) using the standard deviation of price returns. It selects the length with the most stable recent volatility profile.
Calculation:
The selected MA type is calculated using that optimized length. If "Composite" is chosen, all MA types are averaged and smoothed dynamically.
Visualization:
The adaptive MA is plotted on the chart, changing color based on its position relative to price.
📌 Use Cases
Trend-following strategies that adapt to different market conditions.
Traders wanting a high-fidelity composite of multiple MAs.
Analysts interested in visualizing market smoothness without lag-heavy signals.
Coders looking to learn how to build custom indicators from scratch.
🧪 Inputs
MA Type: Choose from 8 MA types or a blended Composite.
Lookback Range: Control min/max and step size for optimization.
Source: Choose any price series (e.g., close, hl2).
⚠️ Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial advice, trading advice, or investment recommendations. Use of this script is at your own risk. Past performance does not guarantee future results. Always perform your own analysis and consult with a qualified financial advisor before making trading decisions.
Yelober - Intraday ETF Dashboard# How to Read the Yelober Intraday ETF Dashboard
The Intraday ETF Dashboard provides a powerful at-a-glance view of sector performance and trading opportunities. Here's how to interpret and use the information:
## Basic Dashboard Reading
### Color-Coding System
- **Green values**: Positive performance or bullish signals
- **Red values**: Negative performance or bearish signals
- **Symbol colors**: Green = buy signal, Red = sell signal, Gray = neutral
### Example 1: Identifying Strong Sectors
If you see XLF (Financials) with:
- Day % showing +2.65% (green background)
- Symbol in green color
- RSI of 58 (not overbought)
**Interpretation**: Financial sector is showing strength and momentum without being overextended. Consider long positions in top financial stocks like JPM or BAC.
### Example 2: Spotting Weakness
If you see XLK (Technology) with:
- Day % showing -1.20% (red background)
- Week % showing -3.50% (red background)
- Symbol in red color
- RSI of 35 (approaching oversold)
**Interpretation**: Technology sector is showing weakness across multiple timeframes. Consider avoiding tech stocks or taking short positions in names like MSFT or AAPL, but be cautious as the low RSI suggests a bounce may be coming.
## Advanced Interpretations
### Example 3: Sector Rotation Detection
If you observe:
- XLE (Energy) showing +2.10% while XLK (Technology) showing -1.50%
- Both sectors' Week % values showing the opposite trend
**Interpretation**: This suggests money is rotating out of technology into energy stocks. This rotation pattern is actionable - consider reducing tech exposure and increasing energy positions (look at XOM, CVX in the Top Stocks column).
### Example 4: RSI Divergences
If you see XLU (Utilities) with:
- Day % showing +0.50% (small positive)
- RSI showing 72 (overbought, red background)
**Interpretation**: Despite positive performance, the high RSI suggests the sector is overextended. This divergence between price and indicator suggests caution - the rally in utilities may be running out of steam.
### Example 5: Relative Strength in Weak Markets
If SPY shows -1.20% but XLP (Consumer Staples) shows +0.30%:
**Interpretation**: Consumer staples are showing defensive strength during market weakness. This is typical risk-off behavior. Consider defensive positions in stocks like PG, KO, or PEP for protection.
## Practical Application Scenarios
### Day Trading Setup
1. **Morning Market Assessment**:
- Check which sectors are green pre-market
- Focus on sectors with Day % > 1% and RSI between 40-70
- Identify 2-3 stocks from the Top Stocks column of the strongest sector
2. **Midday Reversal Hunting**:
- Look for sectors with symbol color changing from red to green
- Confirm with RSI moving away from extremes
- Trade stocks from that sector showing similar pattern changes
### Swing Trading Application
1. **Trend Following**:
- Identify sectors with positive Day % and Week %
- Look for RSI values in uptrend but not overbought (45-65)
- Enter positions in top stocks from these sectors, using daily charts for confirmation
2. **Contrarian Setups**:
- Find sectors with deeply negative Day % but RSI < 30
- Look for divergence (price making new lows but RSI rising)
- Consider counter-trend positions in the stronger stocks within these oversold sectors
## Reading Special Conditions
### Example 6: Risk-Off Environment
If you observe:
- XLP (Consumer Staples) and XLU (Utilities) both green
- XLK (Technology) and XLY (Consumer Disc) both red
- SPY slightly negative
**Interpretation**: Classic risk-off rotation. Investors are moving to safety. Consider defensive positioning and reducing exposure to growth sectors.
### Example 7: Market Breadth Analysis
Count the number of sectors in green vs. red:
- If 7+ sectors are green: Strong bullish breadth, consider aggressive long positioning
- If 7+ sectors are red: Weak market breadth, consider defensive positioning or shorts
- If evenly split: Market is indecisive, focus on specific sector strength instead of broad market exposure
Remember that this dashboard is most effective when combined with broader market analysis and appropriate risk management strategies.
Mariam Smart FlipPurpose
This tool identifies high-probability intraday reversals by detecting when price flips through the daily open after strong early-session commitment.
How It Works
A valid flip occurs when:
The previous daily candle is bullish or bearish
The first hour today continues in the same direction
Then, the price flips back through the daily open with a minimum break threshold (user-defined)
This setup is designed to catch liquidity grabs or fakeouts near the daily open, where early buyers or sellers get trapped after showing commitment
Signal Logic
Buy Flip
Previous day bearish → first hour bearish → price flips above open
Sell Flip
Previous day bullish → first hour bullish → price flips below open
Features
Configurable flip threshold in percentage
Signals only activate after the first hour ends
Daily open line displayed on chart
Simple triangle markers with no visual clutter
Alerts ready to use for automation or notifications
Usage Tips
Use "Once Per Bar" alert mode to get notified immediately when the flip happens
Works best in active markets like FX, indices, or crypto
Adjust threshold based on asset volatility
Suggested stop loss: use the previous daily high for sell flips or the previous daily low for buy flips
Suggested take profit: secure at least 30 pips to aim for a 1:3 risk-to-reward ratio on average
Murrey Math Lines v6Murrey Math Lines v6
This is not just another Murrey Math indicator. It's a complete, ground-up modernization of the classic concept, rebuilt with the latest Pine Script features for unparalleled performance, accuracy, and usability. While preserving the core mathematical genius of T.H. Murrey's system, this version introduces a suite of modern tools designed for today's trader.
What are Murrey Math Lines?
Murrey Math Lines (MML) are a powerful system of support and resistance based on geometric formulas developed by T.H. Murrey. As a derivation of W.D. Gann's observations, Murrey's geometry simplifies Gann's theories into a more accessible application. The core principle is that price action tends to trend and retrace in 1/8th intervals.
These intervals create a "trading octave" with distinct levels, each having its own characteristic behavior:
& - Ultimate Resistance & Support: These lines are the hardest to break. They represent the top and bottom of the expected price range and are prime areas for reversals.
- Major Pivot: This is the most significant level, offering the strongest support and resistance within the octave. Price has a high probability of stopping and reversing here.
& - Strong Pivot/Reversal: These are strong, secondary pivot points where price often struggles to pass through.
& - The Trading Range: The price tends to consolidate between these two lines about 50% of the time. A decisive break outside this range often signals the start of a new trend.
& - Weak Support/Resistance: These levels are weaker, but when price moves too quickly towards them, they can act as initial stopping points or areas for a minor reversal.
& - Extended Octave: These lines show extreme overbought and oversold conditions beyond the primary 0/8 to 8/8 octave.
Modern Enhancements in This Version
Session-Locked Precision: Anchor the Murrey Lines to the start of a specific trading session (e.g., NYSE open). The levels remain constant for the entire session, providing a stable and reliable framework for your daily analysis.
Visual Trading & Reversal Zones: Instead of just lines, this indicator can fill the key trading range (3/8 to 5/8) and reversal zones (0/8-1/8 & 7/8-8/8) with color, giving you an instant visual reference of market sentiment.
Dynamic "Closest Price" Labels: Declutter your chart! The indicator can intelligently display only the label for the Murrey level closest to the current price, keeping your view clean while providing critical information at a glance.
Integrated Alert System: Never miss a key level touch again. Set up alerts for when the price approaches major lines, the trading range, or all lines, customized to your trading style.
Advanced Pine Script Engine: Built on a modern codebase using User-Defined Types and dynamic drawing objects (line, box, label). This ensures the indicator is fast, efficient, and non-repainting, even on lower timeframes.
Intuitive User Interface: Settings are neatly organized into collapsible groups with clear tooltips, making it incredibly easy to customize every aspect of the indicator, from calculation parameters to colors.
A Note on Accuracy
Some of the other Murrey Math indicators on TradingView use different formulas and therefore produce varying results. This version has been carefully checked against MML indicators on other professional platforms to ensure its calculations are accurate and reliable.
Credits
This indicator is a complete overhaul and modernization of the original "MM Lines " script. Full credit for the original calculation logic and concept goes to its author, JRL_6.
BOS mark-out (by Lumiere)Advanced BOS Detection with Strict Swing Confirmation
This indicator implements BOS detection with several unique features:
🔹 Dual-Candle Swing Validation - Unlike most BOS indicators that use single candle swings, this uses a two-candle confirmation for swing highs/lows, analyzing both the candle wicks and body transitions.
🔹 Directional Lock System - Implements a state machine that prevents duplicate signals until an opposite-direction BOS occurs, reducing noise.
🔹 Precision Wick Analysis - Compares wicks between the reversal candle and confirmation candle to identify the true swing point.
🔹 Real-Time Update & Live Market Adaptation – The indicator continuously monitors price action and instantly updates BOS signals as new candles form, ensuring you never miss a BOS.
How It Differs From Other BOS Indicators:
Most public BOS indicators use simple HH/HL or LH/LL detection.
Many don't implement the directional locking mechanism.
Few use the two-candle wick comparison approach.
Wick-Based Precision uses the extreme wicks of two candles (not just the body).
Strict Confirmation requires a close beyond the swing point (no "wick breaks" counted).
Usage Examples:
🟦 Bullish BOS:
A green candle closes, followed by a red candle. This will be the new high, and if the next candle closes above the highest wick of those two, it will be a BOS (only if we had a bearish BOS before)
🟥 Bearish BOS:
A red candle closes, followed by a green candle. This will be the new low, and if the next candle closes below the lowest wick of those two, it will be a BOS (only if we had a Bullish BOS before)
Path of Least ResistancePath of Least Resistance (PLR)
Concept Overview
The Path of Least Resistance indicator identifies key zones on your chart that act like "muddy" or "sticky" areas where price tends to get bogged down, creating choppy and unpredictable price action. Between these zones lie the "empty spaces" - clear paths where price can move freely with momentum and direction.
The Analogy: Muddy Fields vs Open Roads
Think of your chart like a landscape:
🟫 ZONES (Muddy/Sticky Areas)
Fair Value Gaps (FVGs) from higher timeframes
Pivot wick zones from higher timeframe pivots
Areas where price gets "stuck" and churns
Like walking through thick mud - slow, choppy, unpredictable movement
Price action becomes erratic and difficult to trade
🟢 EMPTY SPACES (Open Roads)
The clear areas between zones
Where price can move freely with momentum
Like driving on an open highway - smooth, directional movement
The "Path of Least Resistance" for price movement
Trading Philosophy
AVOID Trading Within Zones:
Price action is typically choppy and unpredictable
Higher probability of false signals and whipsaws
Like trying to drive through mud - you'll get stuck
TRADE Through the Empty Spaces:
Look for moves that travel between zones
Price tends to move with momentum and direction
Higher probability setups with cleaner price action
Like taking the highway instead of back roads
Zone Types Detected
Fair Value Gaps (FVGs)
Imbalances from higher timeframe candles
Areas where price "owes" a return visit
Often act as magnets, creating choppy price action
Pivot Wick Zones
Upper and lower wicks from higher timeframe pivots
Rejection areas where price previously struggled
Often create resistance/support that leads to choppy movement
Color Coding System
The zones dynamically change color based on current price position:
🔴 RED ZONES : Price is below the zone (bearish context)
🟢 GREEN ZONES : Price is above the zone (bullish context)
🔘 GRAY ZONES : Price is within the zone (neutral/choppy area)
The "Mum Trades" Strategy
The best trades - what we call "Mum trades" (trades so obvious even your mum could spot them) - happen in the empty spaces between zones:
✅ High Probability Characteristics:
Clear directional movement between zones
Less noise and false signals
Higher momentum and follow-through
Cleaner technical patterns
❌ Avoid These Areas:
Trading within the muddy zones
Expecting clean moves through sticky areas
Fighting against the natural flow of price
Key Features
Auto Timeframe Detection : Automatically selects appropriate higher timeframe
Dynamic Zone Management : Overlapping zones are automatically cleaned up
Real-time Alerts : Get notified when price enters/exits zones
Visual Clarity : Clean zone display with extending boundaries
How to Use
Identify the Zones : Let the indicator mark the muddy areas
Find the Paths : Look for clear spaces between zones
Plan Your Trades : Target moves that travel through empty space
Avoid the Mud : Stay away from trading within the zones
Follow the Flow : Trade with the path of least resistance
Remember
Price, like water, always seeks the path of least resistance. By identifying where that path is clear (empty spaces) versus where it's obstructed (zones), you can align your trading with the natural flow of the market rather than fighting against it.
The goal is simple: Trade the highways, avoid the mud.
Dynamic Laguerre Filter Bands | OttoThis indicator combines trend-following and volatility analysis by enhancing the traditional Laguerre filter with a dynamic, volatility-adjusted band system. Instead of using fixed thresholds, the bands adapt in real-time to changing market conditions by applying smoothed standard deviation calculations. This design keeps the indicator responsive to significant price movements while effectively filtering out short-term market noise, resulting in more accurate trend identification and breakout signals.
Core Concept
The indicator is built around the following key components:
Laguerre Filter:
The Laguerre filter is designed to smooth out price data by reducing market noise while still being quick enough to detect real changes in price direction. Its goal is to create a clear, smooth trend line that helps traders/investors focus on the overall market trend without getting distracted by small, random price swings.
It uses a parameter called gamma to control how it balances smoothness and responsiveness:
A lower gamma gives more weight to recent price data, making the filter react faster to new price changes. This means the trend line is more sensitive but may also be less smooth and more prone to small fluctuations.
A higher gamma gives more weight to past price data, making the filter smoother and less sensitive to quick changes. This helps reduce noise and produces a steadier trend line, but it also introduces more lag, meaning the filter reacts slower to new price moves.
By adjusting gamma, the Laguerre filter lets you choose the balance between following price changes quickly and having a stable, noise-free trend signal.
Standard Deviation:
shows how much price varies from the mean. In this indicator, it’s used to measure market volatility.
Volatility Bands: The upper and lower bands are based on an EMA-smoothed standard deviation of price. The EMA reduces sudden jumps in volatility, creating smoother and more stable bands that still respond to changing market conditions. These bands are plotted around the Laguerre filter line, expanding and contracting in a controlled way to stay aligned with real market movement while avoiding short-term noise.
Signal Logic:
A long signal is triggered when the close price crosses above the upper band.
A short signal occurs when the close price falls below the lower band.
⚙️ Inputs
Source: Price source used in calculations
Gamma: Adjusts how much the Laguerre filter responds to price changes. Lower gamma values make the filter react more to recent prices, while higher values give more influence to older data, making the line smoother but slower to respond.
Volatility Length: Period used to calculate standard deviation
Volatility Smoothing Length: EMA smoothing length for standard deviation
Multiplier: Scales the width of the bands based on volatility
📈 Visual Output
Laguerre Filter Line: Plots the laguerre filter line, colored dynamically based on signal direction (green for bullish, purple for bearish)
Upper & Lower Bands: Volatility-based bands that adjust with market conditions. (green for bullish, purple for bearish)
Glow Effect: Optional glow layer to enhance visibility of the laguerre filter trend line (green for bullish, purple for bearish)
Bar Coloring: Candlesticks and bar colors reflect the active signal state for fast visual interpretation (green for bullish, purple for bearish)
How to Use
Apply the indicator to your chart and monitor for signal events:
Long Signal: When price closes above the upper band
Short Signal: When price closes below the lower band
🔔 Alerts
This indicator supports optional alert conditions you can enable for:
Long Signal: Close price crossing above the upper band
Short Signal: Close price crossing below the lower band
⚠️ Disclaimer:
This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
PRO Investing - LevelPRO Investing - Level
📊 Dynamic Support/Resistance
This indicator plots the PRO Investing Level, defined as the midpoint between the highest high and lowest low over the past 252 trading days (default lookback period, equivalent to ~1 year). It acts as a key mean-reversion reference level, useful for identifying potential support/resistance zones or market equilibrium levels.
Features:
🕰️ Option to display only today’s level or historical levels.
⚙️ Customizable lookback period for flexibility across timeframes and strategies.
📉 Teal line plotted directly on the chart, highlighting this institutional-grade level.
Ideal for traders looking to anchor price action to significant historical ranges—particularly useful in mean-reversion, breakout, or volatility compression strategies.
VWAP Multi-Timeframe VWAP Multi-Timeframe - Complete Professional Indicator
🚀 WHAT IS IT?
The VWAP Multi-Timeframe is an advanced indicator that combines 5 different VWAP periods in a single tool, providing a complete view of market fair value levels across multiple time scales.
⭐ KEY FEATURES
📊 5 Configurable VWAPs:
🟡 Daily VWAP - Ideal for day trading and intraday operations
🟠 Weekly VWAP - Perfect for swing trading
🔵 Monthly VWAP - Excellent for medium-term analysis
🔴 Quarterly VWAP - Essential for quarterly strategies
🟢 Yearly VWAP - Fundamental for long-term investments
🎯 Multiple Price Sources:
Choose the source that best fits your strategy:
Close - Closing price (most common)
OHLC4 - Complete average (smoother)
HLC3 - Typical price (default)
HL2 - Period midpoint
Open/High/Low - Specific prices
💡 HOW TO USE
For Day Traders:
Use Daily VWAP as main fair value reference
Prices above = buying pressure / Prices below = selling pressure
For Swing Traders:
Combine Weekly and Monthly VWAP to identify trends
Look for confluences between different timeframes
For Investors:
Quarterly and Yearly VWAP show long-term value levels
Excellent for identifying entry points in investments
🔧 TECHNICAL FEATURES
✅ Pine Script v6 - Latest and optimized version
✅ Clean Interface - User-friendly design
TASC 2025.07 Laguerre Filters█ OVERVIEW
This script implements the Laguerre filter and oscillator described by John F. Ehlers in the article "A Tool For Trend Trading, Laguerre Filters" from the July 2025 edition of TASC's Traders' Tips . The new Laguerre filter utilizes the UltimateSmoother filter in place of an exponential moving average (EMA) in its calculation, offering improved responsiveness and reduced lag.
█ CONCEPTS
As Ehlers explains in his article, the Laguerre filter is a form of transversal filter . A transversal filter calculates an output signal using a tapped delay line . It creates multiple delayed versions of an input signal, applies weight to each delay, and then calculates their sum to generate the filtered result.
The Laguerre filter's structure relies on Laguerre polynomials — solutions to a differential equation solved by Edmond Laguerre in the 1800s. When Ehlers analyzed the formula for these polynomials on discrete systems (e.g., financial time series), he found that the first term's expression corresponds to an EMA response, and all subsequent terms correspond to an all-pass response. In contrast to other filter types, an all-pass filter produces phase shift (i.e., delay) in an input signal's components without affecting its amplitude.
Ehlers observed that these characteristics of Laguerre polynomials make them suitable for use in a transversal filter structure, and thus the Laguerre filter was born. However, he notes that EMAs are not great filters in general. As such, to improve on the Laguerre filter's design, Ehlers modified it by replacing the EMA term with his UltimateSmoother filter. The resulting Laguerre filter has significantly reduced lag, achieving a tighter response to market fluctuations while maintaining smoothness. Ehlers suggests that traders can analyze crossings between the UltimateSmoother and this Laguerre filter, or those between two Laguerre filters of different order, for helpful buy and sell signals.
In addition to the Laguerre filter, Ehlers derived a smooth, low-lag oscillator based on the difference between the first and second terms in the modified filter structure, scaled by the root mean square (RMS). The resulting oscillator provides an alternative filtered representation of market data, which can help traders identify swing and mean-reversion signals.
█ USAGE
This indicator calculates both the Laguerre filter and the Laguerre oscillator described in Ehlers' article. It displays the Laguerre filter on the main chart pane and the oscillator in a separate pane.
Users can control the behavior of the filter and oscillator with the inputs in the "Settings/Inputs" tab:
The "Period" input defines the critical period of the UltimateSmoother used in the Laguerre filter and oscillator calculations. Its default value is 30.
The "Gamma" input determines the weighting behavior of the Laguerre filter and oscillator. It accepts a positive value between 0 and 1. Use a lower value for quicker responsiveness to market changes, and a higher value for trends. The default value is 0.5.
The "RMS length" input determines the length of the RMS calculation for oscillator normalization. The default value is 100 bars.
Adaptive Normalized Global Liquidity OscillatorAdaptive Normalized Global Liquidity Oscillator
A dynamic, non-repainting oscillator built on real central bank balance sheet data. This tool visualizes global liquidity shifts by aggregating monetary asset flows from the world’s most influential central banks.
🔍 What This Script Does:
Aggregates Global Liquidity:
Includes Federal Reserve (FED) assets and subtracts liabilities like the Treasury General Account (TGA) and Reverse Repo Facility (RRP), combined with asset positions from the ECB, BOJ, PBC, BOE, and over 10 other central banks. All data is normalized into USD using FX rates.
Adaptive Normalization:
Optimizes the lookback period dynamically based on rate-of-change stability—no fixed lengths, enabling adaptation across macro conditions.
Self-Optimizing Weighting:
Applies inverse standard deviation to balance raw liquidity, smoothed momentum (HMA), and standardized deviation from the mean.
Percentile-Ranked Highlights:
Liquidity readings are ranked relative to history—extremes are visually emphasized using gradient color and adaptive transparency.
Non-Repainting Design:
Data is anchored with bar index awareness and offset techniques, ensuring no forward-looking bias. What you see is what was known at that time.
⚠️ Important Interpretation Note:
This is not a zero-centered oscillator like RSI or MACD. The signal line does not represent neutrality at zero.
Instead, a dynamic baseline is calculated using a rolling mean of scaled liquidity.
0 is irrelevant on its own—true directional signals come from crosses above or below this adaptive baseline.
Even negative values may signal strength if they are rising above the moving average of past liquidity conditions.
✅ What to Watch For:
Crossover Above Dynamic Baseline:
Indicates liquidity is expanding relative to recent conditions—supports a risk-on interpretation.
Crossover Below Dynamic Baseline:
Suggests deteriorating liquidity conditions—may align with risk-off shifts.
Percentile Extremes:
Readings near the top or bottom historical percentiles can act as contrarian or confirmation signals, depending on momentum.
⚙️ How It Works:
Bounded Normalization:
The final oscillator is passed through a tanh function, keeping values within and reducing distortion.
Adaptive Transparency:
The strength of deviations dynamically adjusts plot intensity—visually highlighting stronger liquidity shifts.
Fully Customizable:
Toggle which banks are included, adjust dynamic optimization ranges, and control visual display options for plot and background layers.
🧠 How to Use:
Trend Confirmation:
Sustained rises in the oscillator above baseline suggest underlying monetary support for asset prices.
Macro Turning Points:
Reversals or divergences, especially near OB/OS zones, can foreshadow broader risk regime changes.
Visual Context:
Use the dynamic baseline to see if liquidity is supportive or suppressive relative to its own adaptive history.
📌 Disclaimer:
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always consult a qualified financial advisor before making trading or investment decisions.
Grothendieck-Teichmüller Geometric SynthesisDskyz's Grothendieck-Teichmüller Geometric Synthesis (GTGS)
THEORETICAL FOUNDATION: A SYMPHONY OF GEOMETRIES
The 🎓 GTGS is built upon a revolutionary premise: that market dynamics can be modeled as geometric and topological structures. While not a literal academic implementation—such a task would demand computational power far beyond current trading platforms—it leverages core ideas from advanced mathematical theories as powerful analogies and frameworks for its algorithms. Each component translates an abstract concept into a practical market calculation, distinguishing GTGS by identifying deeper structural patterns rather than relying on standard statistical measures.
1. Grothendieck-Teichmüller Theory: Deforming Market Structure
The Theory : Studies symmetries and deformations of geometric objects, focusing on the "absolute" structure of mathematical spaces.
Indicator Analogy : The calculate_grothendieck_field function models price action as a "deformation" from its immediate state. Using the nth root of price ratios (math.pow(price_ratio, 1.0/prime)), it measures market "shape" stretching or compression, revealing underlying tensions and potential shifts.
2. Topos Theory & Sheaf Cohomology: From Local to Global Patterns
The Theory : A framework for assembling local properties into a global picture, with cohomology measuring "obstructions" to consistency.
Indicator Analogy : The calculate_topos_coherence function uses sine waves (math.sin) to represent local price "sections." Summing these yields a "cohomology" value, quantifying price action consistency. High values indicate coherent trends; low values signal conflict and uncertainty.
3. Tropical Geometry: Simplifying Complexity
The Theory : Transforms complex multiplicative problems into simpler, additive, piecewise-linear ones using min(a, b) for addition and a + b for multiplication.
Indicator Analogy : The calculate_tropical_metric function applies tropical_add(a, b) => math.min(a, b) to identify the "lowest energy" state among recent price points, pinpointing critical support levels non-linearly.
4. Motivic Cohomology & Non-Commutative Geometry
The Theory : Studies deep arithmetic and quantum-like properties of geometric spaces.
Indicator Analogy : The motivic_rank and spectral_triple functions compute weighted sums of historical prices to capture market "arithmetic complexity" and "spectral signature." Higher values reflect structured, harmonic price movements.
5. Perfectoid Spaces & Homotopy Type Theory
The Theory : Abstract fields dealing with p-adic numbers and logical foundations of mathematics.
Indicator Analogy : The perfectoid_conv and type_coherence functions analyze price convergence and path identity, assessing the "fractal dust" of price differences and price path cohesion, adding fractal and logical analysis.
The Combination is Key : No single theory dominates. GTGS ’s Unified Field synthesizes all seven perspectives into a comprehensive score, ensuring signals reflect deep structural alignment across mathematical domains.
🎛️ INPUTS: CONFIGURING THE GEOMETRIC ENGINE
The GTGS offers a suite of customizable inputs, allowing traders to tailor its behavior to specific timeframes, market sectors, and trading styles. Below is a detailed breakdown of key input groups, their functionality, and optimization strategies, leveraging provided tooltips for precision.
Grothendieck-Teichmüller Theory Inputs
🧬 Deformation Depth (Absolute Galois) :
What It Is : Controls the depth of Galois group deformations analyzed in market structure.
How It Works : Measures price action deformations under automorphisms of the absolute Galois group, capturing market symmetries.
Optimization :
Higher Values (15-20) : Captures deeper symmetries, ideal for major trends in swing trading (4H-1D).
Lower Values (3-8) : Responsive to local deformations, suited for scalping (1-5min).
Timeframes :
Scalping (1-5min) : 3-6 for quick local shifts.
Day Trading (15min-1H) : 8-12 for balanced analysis.
Swing Trading (4H-1D) : 12-20 for deep structural trends.
Sectors :
Stocks : Use 8-12 for stable trends.
Crypto : 3-8 for volatile, short-term moves.
Forex : 12-15 for smooth, cyclical patterns.
Pro Tip : Increase in trending markets to filter noise; decrease in choppy markets for sensitivity.
🗼 Teichmüller Tower Height :
What It Is : Determines the height of the Teichmüller modular tower for hierarchical pattern detection.
How It Works : Builds modular levels to identify nested market patterns.
Optimization :
Higher Values (6-8) : Detects complex fractals, ideal for swing trading.
Lower Values (2-4) : Focuses on primary patterns, faster for scalping.
Timeframes :
Scalping : 2-3 for speed.
Day Trading : 4-5 for balanced patterns.
Swing Trading : 5-8 for deep fractals.
Sectors :
Indices : 5-8 for robust, long-term patterns.
Crypto : 2-4 for rapid shifts.
Commodities : 4-6 for cyclical trends.
Pro Tip : Higher towers reveal hidden fractals but may slow computation; adjust based on hardware.
🔢 Galois Prime Base :
What It Is : Sets the prime base for Galois field computations.
How It Works : Defines the field extension characteristic for market analysis.
Optimization :
Prime Characteristics :
2 : Binary markets (up/down).
3 : Ternary states (bull/bear/neutral).
5 : Pentagonal symmetry (Elliott waves).
7 : Heptagonal cycles (weekly patterns).
11,13,17,19 : Higher-order patterns.
Timeframes :
Scalping/Day Trading : 2 or 3 for simplicity.
Swing Trading : 5 or 7 for wave or cycle detection.
Sectors :
Forex : 5 for Elliott wave alignment.
Stocks : 7 for weekly cycle consistency.
Crypto : 3 for volatile state shifts.
Pro Tip : Use 7 for most markets; 5 for Elliott wave traders.
Topos Theory & Sheaf Cohomology Inputs
🏛️ Temporal Site Size :
What It Is : Defines the number of time points in the topological site.
How It Works : Sets the local neighborhood for sheaf computations, affecting cohomology smoothness.
Optimization :
Higher Values (30-50) : Smoother cohomology, better for trends in swing trading.
Lower Values (5-15) : Responsive, ideal for reversals in scalping.
Timeframes :
Scalping : 5-10 for quick responses.
Day Trading : 15-25 for balanced analysis.
Swing Trading : 25-50 for smooth trends.
Sectors :
Stocks : 25-35 for stable trends.
Crypto : 5-15 for volatility.
Forex : 20-30 for smooth cycles.
Pro Tip : Match site size to your average holding period in bars for optimal coherence.
📐 Sheaf Cohomology Degree :
What It Is : Sets the maximum degree of cohomology groups computed.
How It Works : Higher degrees capture complex topological obstructions.
Optimization :
Degree Meanings :
1 : Simple obstructions (basic support/resistance).
2 : Cohomological pairs (double tops/bottoms).
3 : Triple intersections (complex patterns).
4-5 : Higher-order structures (rare events).
Timeframes :
Scalping/Day Trading : 1-2 for simplicity.
Swing Trading : 3 for complex patterns.
Sectors :
Indices : 2-3 for robust patterns.
Crypto : 1-2 for rapid shifts.
Commodities : 3-4 for cyclical events.
Pro Tip : Degree 3 is optimal for most trading; higher degrees for research or rare event detection.
🌐 Grothendieck Topology :
What It Is : Chooses the Grothendieck topology for the site.
How It Works : Affects how local data integrates into global patterns.
Optimization :
Topology Characteristics :
Étale : Finest topology, captures local-global principles.
Nisnevich : A1-invariant, good for trends.
Zariski : Coarse but robust, filters noise.
Fpqc : Faithfully flat, highly sensitive.
Sectors :
Stocks : Zariski for stability.
Crypto : Étale for sensitivity.
Forex : Nisnevich for smooth trends.
Indices : Zariski for robustness.
Timeframes :
Scalping : Étale for precision.
Swing Trading : Nisnevich or Zariski for reliability.
Pro Tip : Start with Étale for precision; switch to Zariski in noisy markets.
Unified Field Configuration Inputs
⚛️ Field Coupling Constant :
What It Is : Sets the interaction strength between geometric components.
How It Works : Controls signal amplification in the unified field equation.
Optimization :
Higher Values (0.5-1.0) : Strong coupling, amplified signals for ranging markets.
Lower Values (0.001-0.1) : Subtle signals for trending markets.
Timeframes :
Scalping : 0.5-0.8 for quick, strong signals.
Swing Trading : 0.1-0.3 for trend confirmation.
Sectors :
Crypto : 0.5-1.0 for volatility.
Stocks : 0.1-0.3 for stability.
Forex : 0.3-0.5 for balance.
Pro Tip : Default 0.137 (fine structure constant) is a balanced starting point; adjust up in choppy markets.
📐 Geometric Weighting Scheme :
What It Is : Determines the framework for combining geometric components.
How It Works : Adjusts emphasis on different mathematical structures.
Optimization :
Scheme Characteristics :
Canonical : Equal weighting, balanced.
Derived : Emphasizes higher-order structures.
Motivic : Prioritizes arithmetic properties.
Spectral : Focuses on frequency domain.
Sectors :
Stocks : Canonical for balance.
Crypto : Spectral for volatility.
Forex : Derived for structured moves.
Indices : Motivic for arithmetic cycles.
Timeframes :
Day Trading : Canonical or Derived for flexibility.
Swing Trading : Motivic for long-term cycles.
Pro Tip : Start with Canonical; experiment with Spectral in volatile markets.
Dashboard and Visual Configuration Inputs
📋 Show Enhanced Dashboard, 📏 Size, 📍 Position :
What They Are : Control dashboard visibility, size, and placement.
How They Work : Display key metrics like Unified Field , Resonance , and Signal Quality .
Optimization :
Scalping : Small size, Bottom Right for minimal chart obstruction.
Swing Trading : Large size, Top Right for detailed analysis.
Sectors : Universal across markets; adjust size based on screen setup.
Pro Tip : Use Large for analysis, Small for live trading.
📐 Show Motivic Cohomology Bands, 🌊 Morphism Flow, 🔮 Future Projection, 🔷 Holographic Mesh, ⚛️ Spectral Flow :
What They Are : Toggle visual elements representing mathematical calculations.
How They Work : Provide intuitive representations of market dynamics.
Optimization :
Timeframes :
Scalping : Enable Morphism Flow and Spectral Flow for momentum.
Swing Trading : Enable all for comprehensive analysis.
Sectors :
Crypto : Emphasize Morphism Flow and Future Projection for volatility.
Stocks : Focus on Cohomology Bands for stable trends.
Pro Tip : Disable non-essential visuals in fast markets to reduce clutter.
🌫️ Field Transparency, 🔄 Web Recursion Depth, 🎨 Mesh Color Scheme :
What They Are : Adjust visual clarity, complexity, and color.
How They Work : Enhance interpretability of visual elements.
Optimization :
Transparency : 30-50 for balanced visibility; lower for analysis.
Recursion Depth : 6-8 for balanced detail; lower for older hardware.
Color Scheme :
Purple/Blue : Analytical focus.
Green/Orange : Trading momentum.
Pro Tip : Use Neon Purple for deep analysis; Neon Green for active trading.
⏱️ Minimum Bars Between Signals :
What It Is : Minimum number of bars required between consecutive signals.
How It Works : Prevents signal clustering by enforcing a cooldown period.
Optimization :
Higher Values (10-20) : Fewer signals, avoids whipsaws, suited for swing trading.
Lower Values (0-5) : More responsive, allows quick reversals, ideal for scalping.
Timeframes :
Scalping : 0-2 bars for rapid signals.
Day Trading : 3-5 bars for balance.
Swing Trading : 5-10 bars for stability.
Sectors :
Crypto : 0-3 for volatility.
Stocks : 5-10 for trend clarity.
Forex : 3-7 for cyclical moves.
Pro Tip : Increase in choppy markets to filter noise.
Hardcoded Parameters
Tropical, Motivic, Spectral, Perfectoid, Homotopy Inputs : Fixed to optimize performance but influence calculations (e.g., tropical_degree=4 for support levels, perfectoid_prime=5 for convergence).
Optimization : Experiment with codebase modifications if advanced customization is needed, but defaults are robust across markets.
🎨 ADVANCED VISUAL SYSTEM: TRADING IN A GEOMETRIC UNIVERSE
The GTTMTSF ’s visuals are direct representations of its mathematics, designed for intuitive and precise trading decisions.
Motivic Cohomology Bands :
What They Are : Dynamic bands ( H⁰ , H¹ , H² ) representing cohomological support/resistance.
Color & Meaning : Colors reflect energy levels ( H⁰ tightest, H² widest). Breaks into H¹ signal momentum; H² touches suggest reversals.
How to Trade : Use for stop-loss/profit-taking. Band bounces with Dashboard confirmation are high-probability setups.
Morphism Flow (Webbing) :
What It Is : White particle streams visualizing market momentum.
Interpretation : Dense flows indicate strong trends; sparse flows signal consolidation.
How to Trade : Follow dominant flow direction; new flows post-consolidation signal trend starts.
Future Projection Web (Fractal Grid) :
What It Is : Fibonacci-period fractal projections of support/resistance.
Color & Meaning : Three-layer lines (white shadow, glow, colored quantum) with labels showing price, topological class, anomaly strength (φ), resonance (ρ), and obstruction ( H¹ ). ⚡ marks extreme anomalies.
How to Trade : Target ⚡/● levels for entries/exits. High-anomaly levels with weakening Unified Field are reversal setups.
Holographic Mesh & Spectral Flow :
What They Are : Visuals of harmonic interference and spectral energy.
How to Trade : Bright mesh nodes or strong Spectral Flow warn of building pressure before price movement.
📊 THE GEOMETRIC DASHBOARD: YOUR MISSION CONTROL
The Dashboard translates complex mathematics into actionable intelligence.
Unified Field & Signals :
FIELD : Master value (-10 to +10), synthesizing all geometric components. Extreme readings (>5 or <-5) signal structural limits, often preceding reversals or continuations.
RESONANCE : Measures harmony between geometric field and price-volume momentum. Positive amplifies bullish moves; negative amplifies bearish moves.
SIGNAL QUALITY : Confidence meter rating alignment. Trade only STRONG or EXCEPTIONAL signals for high-probability setups.
Geometric Components :
What They Are : Breakdown of seven mathematical engines.
How to Use : Watch for convergence. A strong Unified Field is reliable when components (e.g., Grothendieck , Topos , Motivic ) align. Divergence warns of trend weakening.
Signal Performance :
What It Is : Tracks indicator signal performance.
How to Use : Assesses real-time performance to build confidence and understand system behavior.
🚀 DEVELOPMENT & UNIQUENESS: BEYOND CONVENTIONAL ANALYSIS
The GTTMTSF was developed to analyze markets as evolving geometric objects, not statistical time-series.
Why This Is Unlike Anything Else :
Theoretical Depth : Uses geometry and topology, identifying patterns invisible to statistical tools.
Holistic Synthesis : Integrates seven deep mathematical frameworks into a cohesive Unified Field .
Creative Implementation : Translates PhD-level mathematics into functional Pine Script , blending theory and practice.
Immersive Visualization : Transforms charts into dynamic geometric landscapes for intuitive market understanding.
The GTTMTSF is more than an indicator; it’s a new lens for viewing markets, for traders seeking deeper insight into hidden order within chaos.
" Where there is matter, there is geometry. " - Johannes Kepler
— Dskyz , Trade with insight. Trade with anticipation.
BackTestLibLibrary "BackTestLib"
Allows backtesting indicator performance. Tracks typical metrics such as won/loss, profit factor, draw down, etc. Trading View strategy library provides similar (and more comprehensive)
functionality but only works with strategies. This libary was created to address performance tracking within indicators.
Two primary outputs are generated:
1. Summary Table: Displays overall performance metrics for the indicator over the chart's loaded timeframe and history
2. Details Table: Displays a table of individual trade entries and exits. This table can grow larger than the available chart space. It does have a max number of rows supported. I haven't
found a way to add scroll bars or scroll bar equivalents yet.
f_init(data, _defaultStopLoss, _defaultTakeProfit, _useTrailingStop, _useTraingStopToBreakEven, _trailingStopActivation, _trailingStopOffset)
f_init Initialize the backtest data type. Called prior to using the backtester functions
Parameters:
data (backtesterData) : backtesterData to initialize
_defaultStopLoss (float) : Default trade stop loss to apply
_defaultTakeProfit (float) : Default trade take profit to apply
_useTrailingStop (bool) : Trailing stop enabled
_useTraingStopToBreakEven (bool) : When trailing stop active, trailing stop will increase no further than the entry price
_trailingStopActivation (int) : When trailing stop active, trailing will begin once price exceeds base stop loss by this number of points
_trailingStopOffset (int) : When trailing stop active, it will trail the max price achieved by this number of points
Returns: Initialized data set
f_buildResultStr(_resultType, _price, _resultPoints, _numWins, _pointsWon, _numLoss, _pointsLost)
f_buildResultStr Helper function to construct a string of resutling data for exit tooltip labels
Parameters:
_resultType (string)
_price (float)
_resultPoints (float)
_numWins (int)
_pointsWon (float)
_numLoss (int)
_pointsLost (float)
f_buildResultLabel(data, labelVertical, labelOffset, long)
f_buildResultLabel Helper function to construct an Exit label for display on the chart
Parameters:
data (backtesterData)
labelVertical (bool)
labelOffset (int)
long (bool)
f_updateTrailingStop(_entryPrice, _curPrice, _sl, _tp, trailingStopActivationInput, trailingStopOffsetInput, useTrailingStopToBreakEven)
f_updateTrailingStop Helper function to advance the trailing stop as price action dictates
Parameters:
_entryPrice (float)
_curPrice (float)
_sl (float)
_tp (float)
trailingStopActivationInput (float)
trailingStopOffsetInput (float)
useTrailingStopToBreakEven (bool)
Returns: Updated stop loss for current price action
f_enterShort(data, entryPrice, fixedStopLoss)
f_enterShort Helper function to enter a short and collect data necessary for tracking the trade entry
Parameters:
data (backtesterData)
entryPrice (float)
fixedStopLoss (float)
Returns: Updated backtest data
f_enterLong(data, entryPrice, fixedStopLoss)
f_enterLong Helper function to enter a long and collect data necessary for tracking the trade entry
Parameters:
data (backtesterData)
entryPrice (float)
fixedStopLoss (float)
Returns: Updated backtest data
f_exitTrade(data)
f_enterLong Helper function to exit a trade and update/reset tracking data
Parameters:
data (backtesterData)
Returns: Updated backtest data
f_checkTradeConditionForExit(data, condition, curPrice, enableRealTime)
f_checkTradeConditionForExit Helper function to determine if provided condition indicates an exit
Parameters:
data (backtesterData)
condition (bool) : When true trade will exit
curPrice (float)
enableRealTime (bool) : When true trade will evaluate if barstate is relatime or barstate is confirmed; otherwise just checks on is confirmed
Returns: Updated backtest data
f_checkTrade(data, curPrice, curLow, curHigh, enableRealTime)
f_checkTrade Helper function to determine if current price action dictates stop loss or take profit exit
Parameters:
data (backtesterData)
curPrice (float)
curLow (float)
curHigh (float)
enableRealTime (bool) : When true trade will evaluate if barstate is relatime or barstate is confirmed; otherwise just checks on is confirmed
Returns: Updated backtest data
f_fillCell(_table, _column, _row, _title, _value, _bgcolor, _txtcolor, _text_size)
f_fillCell Helper function to construct result table cells
Parameters:
_table (table)
_column (int)
_row (int)
_title (string)
_value (string)
_bgcolor (color)
_txtcolor (color)
_text_size (string)
Returns: Table cell
f_prepareStatsTable(data, drawTesterSummary, drawTesterDetails, summaryTableTextSize, detailsTableTextSize, displayRowZero, summaryTableLocation, detailsTableLocation)
f_fillCell Helper function to populate result table
Parameters:
data (backtesterData)
drawTesterSummary (bool)
drawTesterDetails (bool)
summaryTableTextSize (string)
detailsTableTextSize (string)
displayRowZero (bool)
summaryTableLocation (string)
detailsTableLocation (string)
Returns: Updated backtest data
backtesterData
backtesterData - container for backtest performance metrics
Fields:
tradesArray (array) : Array of strings with entries for each individual trade and its results
pointsBalance (series float) : Running sum of backtest points won/loss results
drawDown (series float) : Running sum of backtest total draw down points
maxDrawDown (series float) : Running sum of backtest total draw down points
maxRunup (series float) : Running sum of max points won over the backtest
numWins (series int) : Number of wins of current backtes set
numLoss (series int) : Number of losses of current backtes set
pointsWon (series float) : Running sum of points won to date
pointsLost (series float) : Running sum of points lost to date
entrySide (series string) : Current entry long/short
tradeActive (series bool) : Indicates if a trade is currently active
tradeComplete (series bool) : Indicates if a trade just exited (due to stop loss or take profit)
entryPrice (series float) : Current trade entry price
entryTime (series int) : Current trade entry time
sl (series float) : Current trade stop loss
tp (series float) : Current trade take profit
defaultStopLoss (series float) : Default trade stop loss to apply
defaultTakeProfit (series float) : Default trade take profit to apply
useTrailingStop (series bool) : Trailing stop enabled
useTrailingStopToBreakEven (series bool) : When trailing stop active, trailing stop will increase no further than the entry price
trailingStopActivation (series int) : When trailing stop active, trailing will begin once price exceeds base stop loss by this number of points
trailingStopOffset (series int) : When trailing stop active, it will trail the max price achieved by this number of points
resultType (series string) : Current trade won/lost
exitPrice (series float) : Current trade exit price
resultPoints (series float) : Current trade points won/lost
summaryTable (series table) : Table to deisplay summary info
tradesTable (series table) : Table to display per trade info
Boring Candles by The School of Dalal StreetThis indicator highlights the "boring" candles. These are candles where the body is less than 50% in length as compared to the high and low length. This allows us to quickly find the lower timeframe demand/supply without switching the chart timeframe. The use case is to quickly find our targets based on lower time frames.
Luma DCA Tracker (BTC)Luma DCA Tracker (BTC) – User Guide
Function
This indicator simulates a regular Bitcoin investment strategy (Dollar Cost Averaging). It calculates and visualizes:
Accumulated BTC amount
Average entry price
Total amount invested
Current portfolio value
Profit/loss in absolute and percentage terms
Settings
Investment per interval
Fixed amount to be invested at each interval (e.g., 100 USD)
Start date
The date when DCA simulation begins
Investment interval
Choose between:
daily, weekly, every 14 days, or monthly
Show investment data
Displays additional chart lines (total invested, value, profit, etc.)
Chart Elements
Orange line: Average DCA entry price
Grey dots: Entry points based on selected interval
Info box (bottom left): Live summary of all key values
Notes
Purchases are simulated at the closing price of each interval
No fees, slippage, or taxes are included
The indicator is a simulation only and not linked to an actual portfolio
