Period Highlighter ProPeriod Highlighter Pro is a versatile Pine Script indicator designed to visually highlight specific time periods on your TradingView charts, making it easier to analyze seasonal patterns, trading sessions, or specific weekdays. With customizable settings for months, weekdays, or intraday time ranges, this tool adapts to your trading strategy, allowing you to focus on key periods with precision.
Features
Flexible Highlight Modes: Choose from three modes to highlight:
Month Range: Highlight specific months or a range (e.g., March to June) for seasonal analysis.
Weekday Range: Highlight specific weekdays (e.g., Mondays or Monday to Wednesday) for weekly pattern analysis.
Time Range: Highlight daily time windows (e.g., 15:30–22:00) for intraday session analysis, restricted to weekdays.
Customizable Timezone: Set any IANA timezone (e.g., America/New_York, Europe/London) or UTC offset to align highlights with your preferred market hours.
Historical Range Control: Define how far back to apply highlights with options for years (Month Range), weeks (Weekday Range), or days (Time Range).
Visual Customization: Choose your highlight color to match your chart style.
User-Friendly Inputs: Intuitive dropdowns and tooltips guide you through configuring each mode, ensuring only relevant settings are adjusted.
How It Works
Select a highlight mode and configure the corresponding settings:
Month Range: Pick a start month and an optional end month (or "Disabled" for a single month) and set the number of years back.
Weekday Range: Choose a start weekday and an optional end weekday (or "Disabled" for a single day) and set the number of weeks back.
Time Range: Specify a start and end time (24-hour format) and the number of weekdays back. The indicator then applies a semi-transparent background color to chart bars that meet your criteria, making it easy to spot relevant periods.
Use Cases
Seasonal Traders: Highlight specific months to analyze recurring market patterns.
Day Traders: Focus on active trading sessions (e.g., New York open) with precise time range highlighting.
Weekly Pattern Analysts: Isolate specific weekdays to study price behavior.
Global Traders: Adjust for any timezone to align with your market of interest.
Why Use Period Highlighter Pro?
This indicator simplifies time-based analysis by providing a clear visual overlay for your chosen periods. Whether you're studying historical trends or focusing on specific trading hours, Period Highlighter Pro offers the flexibility and precision to enhance your chart analysis.
Licensed under the Mozilla Public License 2.0.
Cerca negli script per "豪24配债"
Crypto Options Greeks & Volatility Analyzer [BackQuant]Crypto Options Greeks & Volatility Analyzer
Overview
The Crypto Options Greeks & Volatility Analyzer is a comprehensive analytical tool that calculates Black-Scholes option Greeks up to the third order for Bitcoin and Ethereum options. It integrates implied volatility data from VOLMEX indices and provides multiple visualization layers for options risk analysis.
Quick Introduction to Options Trading
Options are financial derivatives that give the holder the right, but not the obligation, to buy or sell an underlying asset at a predetermined price (strike price) within a specific time period (expiration date). Understanding options requires grasping two fundamental concepts:
Call Options : Give the right to buy the underlying asset at the strike price. Calls increase in value when the underlying price rises above the strike price.
Put Options : Give the right to sell the underlying asset at the strike price. Puts increase in value when the underlying price falls below the strike price.
The Language of Options: Greeks
Options traders use "Greeks" - mathematical measures that describe how an option's price changes in response to various factors:
Delta : How much the option price moves for each $1 change in the underlying
Gamma : How fast delta changes as the underlying moves
Theta : Daily time decay - how much value erodes each day
Vega : Sensitivity to implied volatility changes
Rho : Sensitivity to interest rate changes
These Greeks are essential for understanding risk. Just as a pilot needs instruments to fly safely, options traders need Greeks to navigate market conditions and manage positions effectively.
Why Volatility Matters
Implied volatility (IV) represents the market's expectation of future price movement. High IV means:
Options are more expensive (higher premiums)
Market expects larger price swings
Better for option sellers
Low IV means:
Options are cheaper
Market expects smaller moves
Better for option buyers
This indicator helps you visualize and quantify these critical concepts in real-time.
Back to the Indicator
Key Features & Components
1. Complete Greeks Calculations
The indicator computes all standard Greeks using the Black-Scholes-Merton model adapted for cryptocurrency markets:
First Order Greeks:
Delta (Δ) : Measures the rate of change of option price with respect to underlying price movement. Ranges from 0 to 1 for calls and -1 to 0 for puts.
Vega (ν) : Sensitivity to implied volatility changes, expressed as price change per 1% change in IV.
Theta (Θ) : Time decay measured in dollars per day, showing how much value erodes with each passing day.
Rho (ρ) : Interest rate sensitivity, measuring price change per 1% change in risk-free rate.
Second Order Greeks:
Gamma (Γ) : Rate of change of delta with respect to underlying price, indicating how quickly delta will change.
Vanna : Cross-derivative measuring delta's sensitivity to volatility changes and vega's sensitivity to price changes.
Charm : Delta decay over time, showing how delta changes as expiration approaches.
Vomma (Volga) : Vega's sensitivity to volatility changes, important for volatility trading strategies.
Third Order Greeks:
Speed : Rate of change of gamma with respect to underlying price (∂Γ/∂S).
Zomma : Gamma's sensitivity to volatility changes (∂Γ/∂σ).
Color : Gamma decay over time (∂Γ/∂T).
Ultima : Third-order volatility sensitivity (∂²ν/∂σ²).
2. Implied Volatility Analysis
The indicator includes a sophisticated IV ranking system that analyzes current implied volatility relative to its recent history:
IV Rank : Percentile ranking of current IV within its 30-day range (0-100%)
IV Percentile : Percentage of days in the lookback period where IV was lower than current
IV Regime Classification : Very Low, Low, High, or Very High
Color-Coded Headers : Visual indication of volatility regime in the Greeks table
Trading regime suggestions based on IV rank:
IV Rank > 75%: "Favor selling options" (high premium environment)
IV Rank 50-75%: "Neutral / Sell spreads"
IV Rank 25-50%: "Neutral / Buy spreads"
IV Rank < 25%: "Favor buying options" (low premium environment)
3. Gamma Zones Visualization
Gamma zones display horizontal price levels where gamma exposure is highest:
Purple horizontal lines indicate gamma concentration areas
Opacity scaling : Darker shading represents higher gamma values
Percentage labels : Shows gamma intensity relative to ATM gamma
Customizable zones : 3-10 price levels can be analyzed
These zones are critical for understanding:
Pin risk around expiration
Potential for explosive price movements
Optimal strike selection for gamma trading
Market maker hedging flows
4. Probability Cones (Expected Move)
The probability cones project expected price ranges based on current implied volatility:
1 Standard Deviation (68% probability) : Shown with dashed green/red lines
2 Standard Deviations (95% probability) : Shown with dotted green/red lines
Time-scaled projection : Cones widen as expiration approaches
Lognormal distribution : Accounts for positive skew in asset prices
Applications:
Strike selection for credit spreads
Identifying high-probability profit zones
Setting realistic price targets
Risk management for undefined risk strategies
5. Breakeven Analysis
The indicator plots key price levels for options positions:
White line : Strike price
Green line : Call breakeven (Strike + Premium)
Red line : Put breakeven (Strike - Premium)
These levels update dynamically as option premiums change with market conditions.
6. Payoff Structure Visualization
Optional P&L labels display profit/loss at expiration for various price levels:
Shows P&L at -2 sigma, -1 sigma, ATM, +1 sigma, and +2 sigma price levels
Separate calculations for calls and puts
Helps visualize option payoff diagrams directly on the chart
Updates based on current option premiums
Configuration Options
Calculation Parameters
Asset Selection : BTC or ETH (limited by VOLMEX IV data availability)
Expiry Options : 1D, 7D, 14D, 30D, 60D, 90D, 180D
Strike Mode : ATM (uses current spot) or Custom (manual strike input)
Risk-Free Rate : Adjustable annual rate for discounting calculations
Display Settings
Greeks Display : Toggle first, second, and third-order Greeks independently
Visual Elements : Enable/disable probability cones, gamma zones, P&L labels
Table Customization : Position (6 options) and text size (4 sizes)
Price Levels : Show/hide strike and breakeven lines
Technical Implementation
Data Sources
Spot Prices : INDEX:BTCUSD and INDEX:ETHUSD for underlying prices
Implied Volatility : VOLMEX:BVIV (Bitcoin) and VOLMEX:EVIV (Ethereum) indices
Real-Time Updates : All calculations update with each price tick
Mathematical Framework
The indicator implements the full Black-Scholes-Merton model:
Standard normal distribution approximations using Abramowitz and Stegun method
Proper annualization factors (365-day year)
Continuous compounding for interest rate calculations
Lognormal price distribution assumptions
Alert Conditions
Four categories of automated alerts:
Price-Based : Underlying crossing strike price
Gamma-Based : 50% surge detection for explosive moves
Moneyness : Deep ITM alerts when |delta| > 0.9
Time/Volatility : Near expiration and vega spike warnings
Practical Applications
For Options Traders
Monitor all Greeks in real-time for active positions
Identify optimal entry/exit points using IV rank
Visualize risk through probability cones and gamma zones
Track time decay and plan rolls
For Volatility Traders
Compare IV across different expiries
Identify mean reversion opportunities
Monitor vega exposure across strikes
Track higher-order volatility sensitivities
Conclusion
The Crypto Options Greeks & Volatility Analyzer transforms complex mathematical models into actionable visual insights. By combining institutional-grade Greeks calculations with intuitive overlays like probability cones and gamma zones, it bridges the gap between theoretical options knowledge and practical trading application.
Whether you're:
A directional trader using options for leverage
A volatility trader capturing IV mean reversion
A hedger managing portfolio risk
Or simply learning about options mechanics
This tool provides the quantitative foundation needed for informed decision-making in cryptocurrency options markets.
Remember that options trading involves substantial risk and complexity. The Greeks and visualizations provided by this indicator are tools for analysis - they should be combined with proper risk management, position sizing, and a thorough understanding of options strategies.
As crypto options markets continue to mature and grow, having professional-grade analytics becomes increasingly important. This indicator ensures you're equipped with the same analytical capabilities used by institutional traders, adapted specifically for the unique characteristics of 24/7 cryptocurrency markets.
CAGR 5 & 10 Years, Auto-Detect Timeframe# CAGR 5 & 10 Years, Auto-Detect Timeframe
## Overview
This indicator automatically calculates the **Compound Annual Growth Rate (CAGR)** for 5-year and 10-year periods, adapting intelligently to different asset types and timeframes.
## Key Features
### 🤖 **Smart Market Detection**
- **Automatically detects** if the asset operates 24/7 (crypto, crypto futures) or traditional hours (stocks, forex)
### ⏰ **Multi-Timeframe Support**
**Compatible timeframes**: 1H, 2H, 3H, 4H, 6H, 8H, 12H, 1D, 3D, 1W, 1M, 3M, 6M, 12M
### 📊 **Visual Display**
- **Green line**: 5-year CAGR percentage
- **Blue line**: 10-year CAGR percentage
- **Zero reference line** for easy interpretation
## Use Cases
- **Long-term performance analysis** across different timeframes
- **Cross-asset comparison** with automatic market type adjustment
- **Investment planning** with standardized annual growth rates
- **Historical perspective** on asset performance
Perfect for investors and analysts who need consistent, comparable growth metrics across different assets and market types.
Daily High/Low Close Breakout - GOLD### **Daily High/Low Close Breakout Indicator**
This indicator is a powerful tool for identifying potential breakout opportunities based on the previous day's price action. It's built on a unique time-based logic that defines key support and resistance levels for the trading day.
---
### **How the Indicator Works**
The indicator operates in two main phases:
1. **Calculation Period (00:00 to 16:30 Tehran Time):** The indicator first observes the price action from the start of the day until 16:30. During this time, it records the highest and lowest **closing prices** of all candles. The chart background is shaded gray to visually mark this period.
2. **Trading Period (16:30 to 16:30 the next day):** At 16:30, the highest and lowest close levels are finalized and drawn as horizontal lines. These levels then become the primary breakout zones for the next 24 hours. The indicator will generate signals whenever the price crosses these lines.
---
### **Trading Signals**
The indicator uses a simple and effective crossover logic for its signals:
* **BUY Signal:** A signal is generated when a candle's closing price **crosses above** the high close line.
* **SELL Signal:** A signal is generated when a candle's closing price **crosses below** the low close line.
---
### **Important Usage Guidelines**
For optimal performance, please follow these specific recommendations:
* **Timeframe:** This indicator is designed and optimized to be used exclusively on the **15-minute timeframe**. Using it on other timeframes may produce inconsistent or unreliable results.
* **Primary Asset:** The logic for this indicator was developed and backtested primarily for **Gold (XAUUSD)**. Its performance and win rate have been observed to be the most consistent on this asset.
* **Asset Restriction:** It is strongly recommended to **avoid using this indicator on other currency pairs or assets**, as it has not been optimized for their specific market behavior.
---
### **Disclaimer**
*This indicator is provided for informational and educational purposes only. It is not financial advice. Past performance is not a guarantee of future results. All trading decisions should be based on your own research and risk analysis. Always use proper risk management.*
RSI OB/OS Alert Indicator[CongTrader]📌 RSI OB/OS Alert Indicator by CongTrader
This is a simple yet powerful Relative Strength Index (RSI) indicator designed to help traders identify potential overbought and oversold market conditions using dynamic alerts and clean visual highlights.
🛠️ How to Use
RSI Length: Adjustable (default = 14).
Overbought Level (default = 75): When RSI crosses above this, price may be overextended.
Oversold Level (default = 25): When RSI drops below this, price may be undervalued.
Background will turn green for oversold zones and red for overbought zones.
Use alerts to get notified when RSI enters these critical zones — no need to watch the chart 24/7.
This tool is suitable for:
Scalping
Swing Trading
Range-bound Markets
Momentum Reversals
Works on any timeframe and any asset (Forex, Crypto, Stocks, Indices, Futures).
🔔 Alerts Included
“RSI Overbought” → Triggered when RSI crosses above the overbought level.
“RSI Oversold” → Triggered when RSI crosses below the oversold level.
Setup your alert by right-clicking on the chart or using the TradingView alert panel.
💬 Keywords (for search visibility)
RSI, RSI Alert, RSI Overbought, RSI Oversold, Momentum Indicator, Reversal Signal, RSI Trading, Crypto RSI, Scalping RSI, RSI Tool, RSI Visual, RSI Zones, Technical Indicator, CongTrader
🙏 Thank You
If you find this indicator useful, feel free to give it a thumbs up 👍 or comment below. Your support helps independent script developers like me continue to share free and open-source tools with the community!
⚠️ Disclaimer
This script is for educational purposes only and does not constitute financial advice. Always perform your own research before making trading decisions. Use this tool at your own risk.
✍️ Developed by CongTrader | Follow for more free indicators & tools.
Futures Trade Entry Indicator (MTF)Work in Progress with the help of Claude. Not ready for active trading. Public for help improving. This will be a multi-timeframe futures trading indicator with supply/demand zones, Fair Value Gaps (FVGs), and sophisticated entry/exit logic.I've created a comprehensive Pine Script v6 indicator that matches all your specifications! Here's what the script includes:
## **Key Features Implemented:**
### **🔄 Multi-Timeframe Logic**
- **1H Chart Data**: Detects Supply Zones, Demand Zones, and Fair Value Gaps
- **Current Timeframe**: Monitors for re-entry and confirmation signals
### **📊 Zone Detection**
- **Supply Zones**: Identified using pivot highs with configurable strength
- **Demand Zones**: Identified using pivot lows with touch validation
- **Fair Value Gaps**: Both bullish and bearish FVGs detected automatically
- **Auto-Expiry**: Zones expire after 24 hours (configurable)
### **⚡ Entry Logic**
- **Dual Confirmation Required**:
- ✅ Engulfing candle pattern (bullish/bearish)
- ✅ Market structure shift (HH→LL or LL→HH)
- **Zone Re-entry**: Price must be within identified zones/FVGs
### **🎯 Probability System**
- **Smart Scoring**: Based on zone age, strength, and risk/reward ratio
- **Color-Coded**: Green (High), Yellow (Medium), Red (Low)
- **Real-time Calculation**: Updates with each potential entry
### **🎨 Visual Elements**
- **Colored Zones**: Supply (red), Demand (green), FVGs (blue/orange)
- **Entry Labels**: 🟩 LONG / 🟥 SHORT markers
- **Probability Labels**: Display confidence levels
- **Confirmation Shapes**: Triangle indicators for pattern completion
### **⚙️ Manual Controls**
All the requested toggles are available in the settings panel:
- Show/Hide Supply Zones
- Show/Hide Demand Zones
- Show/Hide FVGs
- Show/Hide Labels
- Show/Hide Probability
- Zone strength and expiry settings
- Custom colors for all elements
### **🔔 Alert System**
- Entry opportunity alerts
- Includes probability assessment
- Ticker symbol identification
## **Usage Instructions:**
1. **Apply to 15m chart** for active trading signals
2. **Configure settings** based on your preferences
3. **Set up alerts** for automated notifications
4. **Monitor probability levels** for trade quality assessment
The script automatically handles the complex multi-timeframe analysis while keeping the interface clean and user-friendly. All zones update dynamically and expire appropriately to avoid clutter.
Would you like me to adjust any specific parameters or add additional features?
Fibonacci Sequence Moving Average [BackQuant]Fibonacci Sequence Moving Average with Adaptive Oscillator
1. Overview
The Fibonacci Sequence Moving Average indicator is a two‑part trading framework that combines a custom moving average built from the famous Fibonacci number set with a fully featured oscillator, normalisation engine and divergence suite. The moving average half delivers an adaptive trend line that respects natural market rhythms, while the oscillator half translates that trend information into a bounded momentum stream that is easy to read, easy to compare across assets and rich in confluence signals. Everything from weighting logic to colour palettes can be customised, so the tool comfortably fits scalpers zooming into one‑minute candles as well as position traders running multi‑month trend following campaigns.
2. Core Calculation
Fibonacci periods – The default length array is 5, 8, 13, 21, 34. A single multiplier input lets you scale the whole family up or down without breaking the golden‑ratio spacing. For example a multiplier of 3 yields 15, 24, 39, 63, 102.
Component averages – Each period is passed through Simple Moving Average logic to produce five baseline curves (ma1 through ma5).
Weighting methods – You decide how those five values are blended:
• Equal weighting treats every curve the same.
• Linear weighting applies factors 1‑to‑5 so the slowest curve counts five times as much as the fastest.
• Exponential weighting doubles each step for a fast‑reacting yet still smooth line.
• Fibonacci weighting multiplies each curve by its own period value, honouring the spirit of ratio mathematics.
Smoothing engine – The blended average is then smoothed a second time with your choice of SMA, EMA, DEMA, TEMA, RMA, WMA or HMA. A short smoothing length keeps the result lively, while longer lengths create institution‑grade glide paths that act like dynamic support and resistance.
3. Oscillator Construction
Once the smoothed Fib MA is in place, the script generates a raw oscillator value in one of three flavours:
• Distance – Percentage distance between price and the average. Great for mean‑reversion.
• Momentum – Percentage change of the average itself. Ideal for trend acceleration studies.
• Relative – Distance divided by Average True Range for volatility‑aware scaling.
That raw series is pushed through a look‑back normaliser that rescales every reading into a fixed −100 to +100 window. The normalisation window defaults to 100 bars but can be tightened for fast markets or expanded to capture long regimes.
4. Visual Layer
The oscillator line is gradient‑coloured from deep red through sky blue into bright green, so you can spot subtle momentum shifts with peripheral vision alone. There are four horizontal guide lines: Extreme Bear at −50, Bear Threshold at −20, Bull Threshold at +20 and Extreme Bull at +50. Soft fills above and below the thresholds reinforce the zones without cluttering the chart.
The smoothed Fib MA can be plotted directly on price for immediate trend context, and each of the five component averages can be revealed for educational or research purposes. Optional bar‑painting mirrors oscillator polarity, tinting candles green when momentum is bullish and red when momentum is bearish.
5. Divergence Detection
The script automatically looks for four classes of divergences between price pivots and oscillator pivots:
Regular Bullish, signalling a possible bottom when price prints a lower low but the oscillator prints a higher low.
Hidden Bullish, often a trend‑continuation cue when price makes a higher low while the oscillator slips to a lower low.
Regular Bearish, marking potential tops when price carves a higher high yet the oscillator steps down.
Hidden Bearish, hinting at ongoing downside when price posts a lower high while the oscillator pushes to a higher high.
Each event is tagged with an ℝ or ℍ label at the oscillator pivot, colour‑coded for clarity. Look‑back distances for left and right pivots are fully adjustable so you can fine‑tune sensitivity.
6. Alerts
Five ready‑to‑use alert conditions are included:
• Bullish when the oscillator crosses above +20.
• Bearish when it crosses below −20.
• Extreme Bullish when it pops above +50.
• Extreme Bearish when it dives below −50.
• Zero Cross for momentum inflection.
Attach any of these to TradingView notifications and stay updated without staring at charts.
7. Practical Applications
Swing trading trend filter – Plot the smoothed Fib MA on daily candles and only trade in its direction. Enter on oscillator retracements to the 0 line.
Intraday reversal scouting – On short‑term charts let Distance mode highlight overshoots beyond ±40, then fade those moves back to mean.
Volatility breakout timing – Use Relative mode during earnings season or crypto news cycles to spot momentum surges that adjust for changing ATR.
Divergence confirmation – Layer the oscillator beneath price structure to validate double bottoms, double tops and head‑and‑shoulders patterns.
8. Input Summary
• Source, Fibonacci multiplier, weighting method, smoothing length and type
• Oscillator calculation mode and normalisation look‑back
• Divergence look‑back settings and signal length
• Show or hide options for every visual element
• Full colour and line width customisation
9. Best Practices
Avoid using tiny multipliers on illiquid assets where the shortest Fibonacci window may drop under three bars. In strong trends reduce divergence sensitivity or you may see false counter‑trend flags. For portfolio scanning set oscillator to Momentum mode, hide thresholds and colour bars only, which turns the indicator into a heat‑map that quickly highlights leaders and laggards.
10. Final Notes
The Fibonacci Sequence Moving Average indicator seeks to fuse the mathematical elegance of the golden ratio with modern signal‑processing techniques. It is not a standalone trading system, rather a multi‑purpose information layer that shines when combined with market structure, volume analysis and disciplined risk management. Always test parameters on historical data, be mindful of slippage and remember that past performance is never a guarantee of future results. Trade wisely and enjoy the harmony of Fibonacci mathematics in your technical toolkit.
Info TableOverview
The Info Table V1 is a versatile TradingView indicator tailored for intraday futures traders, particularly those focusing on MESM2 (Micro E-mini S&P 500 futures) on 1-minute charts. It presents essential market insights through two customizable tables: the Main Table for predictive and macro metrics, and the New Metrics Table for momentum and volatility indicators. Designed for high-activity sessions like 9:30 AM–11:00 AM CDT, this tool helps traders assess price alignment, sentiment, and risk in real-time. Metrics update dynamically (except weekly COT data), with optional alerts for key conditions like volatility spikes or momentum shifts.
This indicator builds on foundational concepts like linear regression for predictions and adapts open-source elements for enhanced functionality. Gradient code is adapted from TradingView's Color Library. QQE logic is adapted from LuxAlgo's QQE Weighted Oscillator, licensed under CC BY-NC-SA 4.0. The script is released under the Mozilla Public License 2.0.
Key Features
Two Customizable Tables: Positioned independently (e.g., top-right for Main, bottom-right for New Metrics) with toggle options to show/hide for a clutter-free chart.
Gradient Coloring: User-defined high/low colors (default green/red) for quick visual interpretation of extremes, such as overbought/oversold or high volatility.
Arrows for Directional Bias: In the New Metrics Table, up (↑) or down (↓) arrows appear in value cells based on metric thresholds (top/bottom 25% of range), indicating bullish/high or bearish/low conditions.
Consensus Highlighting: The New Metrics Table's title cells ("Metric" and "Value") turn green if all arrows are ↑ (strong bullish consensus), red if all are ↓ (strong bearish consensus), or gray otherwise.
Predicted Price Plot: Optional line (default blue) overlaying the ML-predicted price for visual comparison with actual price action.
Alerts: Notifications for high/low Frahm Volatility (≥8 or ≤3) and QQE Bias crosses (bullish/bearish momentum shifts).
Main Table Metrics
This table focuses on predictive, positional, and macro insights:
ML-Predicted Price: A linear regression forecast using normalized price, volume, and RSI over a customizable lookback (default 500 bars). Gradient scales from low (red) to high (green) relative to the current price ± threshold (default 100 points).
Deviation %: Percentage difference between current price and predicted price. Gradient highlights extremes (±0.5% default threshold), signaling potential overextensions.
VWAP Deviation %: Percentage difference from Volume Weighted Average Price (VWAP). Gradient indicates if price is above (green) or below (red) fair value (±0.5% default).
FRED UNRATE % Change: Percentage change in U.S. unemployment rate (via FRED data). Cell turns red for increases (economic weakness), green for decreases (strength), gray if zero or disabled.
Open Interest: Total open MESM2 futures contracts. Gradient scales from low (red) to high (green) up to a hardcoded 300,000 threshold, reflecting market participation.
COT Commercial Long/Short: Weekly Commitment of Traders data for commercial positions. Long cell green if longs > shorts (bullish institutional sentiment); Short cell red if shorts > longs (bearish); gray otherwise.
New Metrics Table Metrics
This table emphasizes technical momentum and volatility, with arrows for quick bias assessment:
QQE Bias: Smoothed RSI vs. trailing stop (default length 14, factor 4.236, smooth 5). Green for bullish (RSI > stop, ↑ arrow), red for bearish (RSI < stop, ↓ arrow), gray for neutral.
RSI: Relative Strength Index (default period 14). Gradient from oversold (red, <30 + threshold offset, ↓ arrow if ≤40) to overbought (green, >70 - offset, ↑ arrow if ≥60).
ATR Volatility: Score (1–20) based on Average True Range (default period 14, lookback 50). High scores (green, ↑ if ≥15) signal swings; low (red, ↓ if ≤5) indicate calm.
ADX Trend: Average Directional Index (default period 14). Gradient from weak (red, ↓ if ≤0.25×25 threshold) to strong trends (green, ↑ if ≥0.75×25).
Volume Momentum: Score (1–20) comparing current to historical volume (lookback 50). High (green, ↑ if ≥15) suggests pressure; low (red, ↓ if ≤5) implies weakness.
Frahm Volatility: Score (1–20) from true range over a window (default 24 hours, multiplier 9). Dynamic gradient (green/red/yellow); ↑ if ≥7.5, ↓ if ≤2.5.
Frahm Avg Candle (Ticks): Average candle size in ticks over the window. Blue gradient (or dynamic green/red/yellow); ↑ if ≥0.75 percentile, ↓ if ≤0.25.
Arrows trigger on metric-specific logic (e.g., RSI ≥60 for ↑), providing directional cues without strict color ties.
Customization Options
Adapt the indicator to your strategy:
ML Inputs: Lookback (10–5000 bars) and RSI period (2+) for prediction sensitivity—shorter for volatility, longer for trends.
Timeframes: Individual per metric (e.g., 1H for QQE Bias to match higher frames; blank for chart timeframe).
Thresholds: Adjust gradients and arrows (e.g., Deviation 0.1–5%, ADX 0–100, RSI overbought/oversold).
QQE Settings: Length, factor, and smooth for fine-tuned momentum.
Data Toggles: Enable/disable FRED, Open Interest, COT for focus (e.g., disable macro for pure intraday).
Frahm Options: Window hours (1+), scale multiplier (1–10), dynamic colors for avg candle.
Plot/Table: Line color, positions, gradients, and visibility.
Ideal Use Case
Perfect for MESM2 scalpers and trend traders. Use the Main Table for entry confirmation via predicted deviations and institutional positioning. Leverage the New Metrics Table arrows for short-term signals—enter bullish on green consensus (all ↑), avoid chop on low volatility. Set alerts to catch shifts without constant monitoring.
Why It's Valuable
Info Table V1 consolidates diverse metrics into actionable visuals, answering critical questions: Is price mispriced? Is momentum aligning? Is volatility manageable? With real-time updates, consensus highlights, and extensive customization, it enhances precision in fast markets, reducing guesswork for confident trades.
Note: Optimized for futures; some metrics (OI, COT) unavailable on non-futures symbols. Test on demo accounts. No financial advice—use at your own risk.
The provided script reuses open-source elements from TradingView's Color Library and LuxAlgo's QQE Weighted Oscillator, as noted in the script comments and description. Credits are appropriately given in both the description and code comments, satisfying the requirement for attribution.
Regarding significant improvements and proportion:
The QQE logic comprises approximately 15 lines of code in a script exceeding 400 lines, representing a small proportion (<5%).
Adaptations include integration with multi-timeframe support via request.security, user-customizable inputs for length, factor, and smooth, and application within a broader table-based indicator for momentum bias display (with color gradients, arrows, and alerts). This extends the original QQE beyond standalone oscillator use, incorporating it as one of seven metrics in the New Metrics Table for confluence analysis (e.g., consensus highlighting when all metrics align). These are functional enhancements, not mere stylistic or variable changes.
The Color Library usage is via official import (import TradingView/Color/1 as Color), leveraging built-in gradient functions without copying code, and applied to enhance visual interpretation across multiple metrics.
The script complies with the rules: reused code is minimal, significantly improved through integration and expansion, and properly credited. It qualifies for open-source publication under the Mozilla Public License 2.0, as stated.
VoVix DEVMA🌌 VoVix DEVMA: A Deep Dive into Second-Order Volatility Dynamics
Welcome to VoVix+, a sophisticated trading framework that transcends traditional price analysis. This is not merely another indicator; it is a complete system designed to dissect and interpret the very fabric of market volatility. VoVix+ operates on the principle that the most powerful signals are not found in price alone, but in the behavior of volatility itself. It analyzes the rate of change, the momentum, and the structure of market volatility to identify periods of expansion and contraction, providing a unique edge in anticipating major market moves.
This document will serve as your comprehensive guide, breaking down every mathematical component, every user input, and every visual element to empower you with a profound understanding of how to harness its capabilities.
🔬 THEORETICAL FOUNDATION: THE MATHEMATICS OF MARKET DYNAMICS
VoVix+ is built upon a multi-layered mathematical engine designed to measure what we call "second-order volatility." While standard indicators analyze price, and first-order volatility indicators (like ATR) analyze the range of price, VoVix+ analyzes the dynamics of the volatility itself. This provides insight into the market's underlying state of stability or chaos.
1. The VoVix Score: Measuring Volatility Thrust
The core of the system begins with the VoVix Score. This is a normalized measure of volatility acceleration or deceleration.
Mathematical Formula:
VoVix Score = (ATR(fast) - ATR(slow)) / (StDev(ATR(fast)) + ε)
Where:
ATR(fast) is the Average True Range over a short period, representing current, immediate volatility.
ATR(slow) is the Average True Range over a longer period, representing the baseline or established volatility.
StDev(ATR(fast)) is the Standard Deviation of the fast ATR, which measures the "noisiness" or consistency of recent volatility.
ε (epsilon) is a very small number to prevent division by zero.
Market Implementation:
Positive Score (Expansion): When the fast ATR is significantly higher than the slow ATR, it indicates a rapid increase in volatility. The market is "stretching" or expanding.
Negative Score (Contraction): When the fast ATR falls below the slow ATR, it indicates a decrease in volatility. The market is "coiling" or contracting.
Normalization: By dividing by the standard deviation, we normalize the score. This turns it into a standardized measure, allowing us to compare volatility thrust across different market conditions and timeframes. A score of 2.0 in a quiet market means the same, relatively, as a score of 2.0 in a volatile market.
2. Deviation Analysis (DEV): Gauging Volatility's Own Volatility
The script then takes the analysis a step further. It calculates the standard deviation of the VoVix Score itself.
Mathematical Formula:
DEV = StDev(VoVix Score, lookback_period)
Market Implementation:
This DEV value represents the magnitude of chaos or stability in the market's volatility dynamics. A high DEV value means the volatility thrust is erratic and unpredictable. A low DEV value suggests the change in volatility is smooth and directional.
3. The DEVMA Crossover: Identifying Regime Shifts
This is the primary signal generator. We take two moving averages of the DEV value.
Mathematical Formula:
fastDEVMA = SMA(DEV, fast_period)
slowDEVMA = SMA(DEV, slow_period)
The Core Signal:
The strategy triggers on the crossover and crossunder of these two DEVMA lines. This is a profound concept: we are not looking at a moving average of price or even of volatility, but a moving average of the standard deviation of the normalized rate of change of volatility.
Bullish Crossover (fastDEVMA > slowDEVMA): This signals that the short-term measure of volatility's chaos is increasing relative to the long-term measure. This often precedes a significant market expansion and is interpreted as a bullish volatility regime.
Bearish Crossunder (fastDEVMA < slowDEVMA): This signals that the short-term measure of volatility's chaos is decreasing. The market is settling down or contracting, often leading to trending moves or range consolidation.
⚙️ INPUTS MENU: CONFIGURING YOUR ANALYSIS ENGINE
Every input has been meticulously designed to give you full control over the strategy's behavior. Understanding these settings is key to adapting VoVix+ to your specific instrument, timeframe, and trading style.
🌀 VoVix DEVMA Configuration
🧬 Deviation Lookback: This sets the lookback period for calculating the DEV value. It defines the window for measuring the stability of the VoVix Score. A shorter value makes the system highly reactive to recent changes in volatility's character, ideal for scalping. A longer value provides a smoother, more stable reading, better for identifying major, long-term regime shifts.
⚡ Fast VoVix Length: This is the lookback period for the fastDEVMA. It represents the short-term trend of volatility's chaos. A smaller number will result in a faster, more sensitive signal line that reacts quickly to market shifts.
🐌 Slow VoVix Length: This is the lookback period for the slowDEVMA. It represents the long-term, baseline trend of volatility's chaos. A larger number creates a more stable, slower-moving anchor against which the fast line is compared.
How to Optimize: The relationship between the Fast and Slow lengths is crucial. A wider gap (e.g., 20 and 60) will result in fewer, but potentially more significant, signals. A narrower gap (e.g., 25 and 40) will generate more frequent signals, suitable for more active trading styles.
🧠 Adaptive Intelligence
🧠 Enable Adaptive Features: When enabled, this activates the strategy's performance tracking module. The script will analyze the outcome of its last 50 trades to calculate a dynamic win rate.
⏰ Adaptive Time-Based Exit: If Enable Adaptive Features is on, this allows the strategy to adjust its Maximum Bars in Trade setting based on performance. It learns from the average duration of winning trades. If winning trades tend to be short, it may shorten the time exit to lock in profits. If winners tend to run, it will extend the time exit, allowing trades more room to develop. This helps prevent the strategy from cutting winning trades short or holding losing trades for too long.
⚡ Intelligent Execution
📊 Trade Quantity: A straightforward input that defines the number of contracts or shares for each trade. This is a fixed value for consistent position sizing.
🛡️ Smart Stop Loss: Enables the dynamic stop-loss mechanism.
🎯 Stop Loss ATR Multiplier: Determines the distance of the stop loss from the entry price, calculated as a multiple of the current 14-period ATR. A higher multiplier gives the trade more room to breathe but increases risk per trade. A lower multiplier creates a tighter stop, reducing risk but increasing the chance of being stopped out by normal market noise.
💰 Take Profit ATR Multiplier: Sets the take profit target, also as a multiple of the ATR. A common practice is to set this higher than the Stop Loss multiplier (e.g., a 2:1 or 3:1 reward-to-risk ratio).
🏃 Use Trailing Stop: This is a powerful feature for trend-following. When enabled, instead of a fixed stop loss, the stop will trail behind the price as the trade moves into profit, helping to lock in gains while letting winners run.
🎯 Trail Points & 📏 Trail Offset ATR Multipliers: These control the trailing stop's behavior. Trail Points defines how much profit is needed before the trail activates. Trail Offset defines how far the stop will trail behind the current price. Both are based on ATR, making them fully adaptive to market volatility.
⏰ Maximum Bars in Trade: This is a time-based stop. It forces an exit if a trade has been open for a specified number of bars, preventing positions from being held indefinitely in stagnant markets.
⏰ Session Management
These inputs allow you to confine the strategy's trading activity to specific market hours, which is crucial for day trading instruments that have defined high-volume sessions (e.g., stock market open).
🎨 Visual Effects & Dashboard
These toggles give you complete control over the on-chart visuals and the dashboard. You can disable any element to declutter your chart or focus only on the information that matters most to you.
📊 THE DASHBOARD: YOUR AT-A-GLANCE COMMAND CENTER
The dashboard centralizes all critical information into one compact, easy-to-read panel. It provides a real-time summary of the market state and strategy performance.
🎯 VOVIX ANALYSIS
Fast & Slow: Displays the current numerical values of the fastDEVMA and slowDEVMA. The color indicates their direction: green for rising, red for falling. This lets you see the underlying momentum of each line.
Regime: This is your most important environmental cue. It tells you the market's current state based on the DEVMA relationship. 🚀 EXPANSION (Green) signifies a bullish volatility regime where explosive moves are more likely. ⚛️ CONTRACTION (Purple) signifies a bearish volatility regime, where the market may be consolidating or entering a smoother trend.
Quality: Measures the strength of the last signal based on the magnitude of the DEVMA difference. An ELITE or STRONG signal indicates a high-conviction setup where the crossover had significant force.
PERFORMANCE
Win Rate & Trades: Displays the historical win rate of the strategy from the backtest, along with the total number of closed trades. This provides immediate feedback on the strategy's historical effectiveness on the current chart.
EXECUTION
Trade Qty: Shows your configured position size per trade.
Session: Indicates whether trading is currently OPEN (allowed) or CLOSED based on your session management settings.
POSITION
Position & PnL: Displays your current position (LONG, SHORT, or FLAT) and the real-time Profit or Loss of the open trade.
🧠 ADAPTIVE STATUS
Stop/Profit Mult: In this simplified version, these are placeholders. The primary adaptive feature currently modifies the time-based exit, which is reflected in how long trades are held on the chart.
🎨 THE VISUAL UNIVERSE: DECIPHERING MARKET GEOMETRY
The visuals are not mere decorations; they are geometric representations of the underlying mathematical concepts, designed to give you an intuitive feel for the market's state.
The Core Lines:
FastDEVMA (Green/Maroon Line): The primary signal line. Green when rising, indicating an increase in short-term volatility chaos. Maroon when falling.
SlowDEVMA (Aqua/Orange Line): The baseline. Aqua when rising, indicating a long-term increase in volatility chaos. Orange when falling.
🌊 Morphism Flow (Flowing Lines with Circles):
What it represents: This visualizes the momentum and strength of the fastDEVMA. The width and intensity of the "beam" are proportional to the signal strength.
Interpretation: A thick, steep, and vibrant flow indicates powerful, committed momentum in the current volatility regime. The floating '●' particles represent kinetic energy; more particles suggest stronger underlying force.
📐 Homotopy Paths (Layered Transparent Boxes):
What it represents: These layered boxes are centered between the two DEVMA lines. Their height is determined by the DEV value.
Interpretation: This visualizes the overall "volatility of volatility." Wider boxes indicate a chaotic, unpredictable market. Narrower boxes suggest a more stable, predictable environment.
🧠 Consciousness Field (The Grid):
What it represents: This grid provides a historical lookback at the DEV range.
Interpretation: It maps the recent "consciousness" or character of the market's volatility. A consistently wide grid suggests a prolonged period of chaos, while a narrowing grid can signal a transition to a more stable state.
📏 Functorial Levels (Projected Horizontal Lines):
What it represents: These lines extend from the current fastDEVMA and slowDEVMA values into the future.
Interpretation: Think of these as dynamic support and resistance levels for the volatility structure itself. A crossover becomes more significant if it breaks cleanly through a prior established level.
🌊 Flow Boxes (Spaced Out Boxes):
What it represents: These are compact visual footprints of the current regime, colored green for Expansion and red for Contraction.
Interpretation: They provide a quick, at-a-glance confirmation of the dominant volatility flow, reinforcing the background color.
Background Color:
This provides an immediate, unmistakable indication of the current volatility regime. Light Green for Expansion and Light Aqua/Blue for Contraction, allowing you to assess the market environment in a split second.
📊 BACKTESTING PERFORMANCE REVIEW & ANALYSIS
The following is a factual, transparent review of a backtest conducted using the strategy's default settings on a specific instrument and timeframe. This information is presented for educational purposes to demonstrate how the strategy's mechanics performed over a historical period. It is crucial to understand that these results are historical, apply only to the specific conditions of this test, and are not a guarantee or promise of future performance. Market conditions are dynamic and constantly change.
Test Parameters & Conditions
To ensure the backtest reflects a degree of real-world conditions, the following parameters were used. The goal is to provide a transparent baseline, not an over-optimized or unrealistic scenario.
Instrument: CME E-mini Nasdaq 100 Futures (NQ1!)
Timeframe: 5-Minute Chart
Backtesting Range: March 24, 2024, to July 09, 2024
Initial Capital: $100,000
Commission: $0.62 per contract (A realistic cost for futures trading).
Slippage: 3 ticks per trade (A conservative setting to account for potential price discrepancies between order placement and execution).
Trade Size: 1 contract per trade.
Performance Overview (Historical Data)
The test period generated 465 total trades , providing a statistically significant sample size for analysis, which is well above the recommended minimum of 100 trades for a strategy evaluation.
Profit Factor: The historical Profit Factor was 2.663 . This metric represents the gross profit divided by the gross loss. In this test, it indicates that for every dollar lost, $2.663 was gained.
Percent Profitable: Across all 465 trades, the strategy had a historical win rate of 84.09% . While a high figure, this is a historical artifact of this specific data set and settings, and should not be the sole basis for future expectations.
Risk & Trade Characteristics
Beyond the headline numbers, the following metrics provide deeper insight into the strategy's historical behavior.
Sortino Ratio (Downside Risk): The Sortino Ratio was 6.828 . Unlike the Sharpe Ratio, this metric only measures the volatility of negative returns. A higher value, such as this one, suggests that during this test period, the strategy was highly efficient at managing downside volatility and large losing trades relative to the profits it generated.
Average Trade Duration: A critical characteristic to understand is the strategy's holding period. With an average of only 2 bars per trade , this configuration operates as a very short-term, or scalping-style, system. Winning trades averaged 2 bars, while losing trades averaged 4 bars. This indicates the strategy's logic is designed to capture quick, high-probability moves and exit rapidly, either at a profit target or a stop loss.
Conclusion and Final Disclaimer
This backtest demonstrates one specific application of the VoVix+ framework. It highlights the strategy's behavior as a short-term system that, in this historical test on NQ1!, exhibited a high win rate and effective management of downside risk. Users are strongly encouraged to conduct their own backtests on different instruments, timeframes, and date ranges to understand how the strategy adapts to varying market structures. Past performance is not indicative of future results, and all trading involves significant risk.
🔧 THE DEVELOPMENT PHILOSOPHY: FROM VOLATILITY TO CLARITY
The journey to create VoVix+ began with a simple question: "What drives major market moves?" The answer is often not a change in price direction, but a fundamental shift in market volatility. Standard indicators are reactive to price. We wanted to create a system that was predictive of market state. VoVix+ was designed to go one level deeper—to analyze the behavior, character, and momentum of volatility itself.
The challenge was twofold. First, to create a robust mathematical model to quantify these abstract concepts. This led to the multi-layered analysis of ATR differentials and standard deviations. Second, to make this complex data intuitive and actionable. This drove the creation of the "Visual Universe," where abstract mathematical values are translated into geometric shapes, flows, and fields. The adaptive system was intentionally kept simple and transparent, focusing on a single, impactful parameter (time-based exits) to provide performance feedback without becoming an inscrutable "black box." The result is a tool that is both profoundly deep in its analysis and remarkably clear in its presentation.
⚠️ RISK DISCLAIMER AND BEST PRACTICES
VoVix+ is an advanced analytical tool, not a guarantee of future profits. All financial markets carry inherent risk. The backtesting results shown by the strategy are historical and do not guarantee future performance. This strategy incorporates realistic commission and slippage settings by default, but market conditions can vary. Always practice sound risk management, use position sizes appropriate for your account equity, and never risk more than you can afford to lose. It is recommended to use this strategy as part of a comprehensive trading plan. This was developed specifically for Futures
"The prevailing wisdom is that markets are always right. I take the opposite view. I assume that markets are always wrong. Even if my assumption is occasionally wrong, I use it as a working hypothesis."
— George Soros
— Dskyz, Trade with insight. Trade with anticipation.
Time Period Highlighter V2This indicator highlights custom time periods on any intraday chart in TradingView, making it easier to visualize your preferred trading sessions.
You can define up to three separate time ranges per day, each with precise start and end times down to the minute (e.g., 08:30 - 12:15, 14:00 - 16:45, and 20:00 - 22:30). The indicator shades the background of your chart during these periods, helping you quickly identify when you're most active or when specific market conditions occur.
Key Features:
Set start and end times (hours and minutes) for up to three trading sessions.
Automatically highlights these periods across any intraday timeframe.
Uses 24-hour time format aligned with your TradingView chart timezone.
Perfect for day traders, scalpers, or anyone needing clear visual cues for their trading windows.
This tool is especially useful for reviewing trading strategies, backtesting, or ensuring you're focusing on high-probability market hours.
Tip: Double-check that your chart timezone matches your desired session times for accurate highlighting.
Non-Lagging Longevity Zones [BigBeluga]🔵 OVERVIEW
A clean, non-lagging system for identifying price zones that persist over time—ranking them visually based on how long they survive without being invalidated.
Non-Lagging Longevity Zones uses non-lagging pivots to automatically build upper and lower zones that reflect key resistance and support. These zones are kept alive as long as price respects them and are instantly removed when invalidated. The indicator assigns a unique lifespan label to each zone in Days (D), Months (M), or Years (Y), providing instant context for historical relevance.
🔵 CONCEPTS
Non-Lag Pivot Detection: Detects upper and lower pivots using non-lagging swing identification (highest/lowest over length period).
h = ta.highest(len)
l = ta.lowest(len)
high_pivot = high == h and high < h
low_pivot = low == l and low > l
Longevity Ranking: Zones are preserved as long as price doesn't breach them. Levels that remain intact grow in visual intensity.
Time-Based Weighting: Each zone is labeled with its lifespan in days , emphasizing how long it has survived.
duration = last_bar_index - start
days_ = int(duration*(timeframe.in_seconds("")/60/60/24))
days = days_ >= 365 ? int(days_ / 365) : days_ >= 30 ? int(days_ / 30) : days_
marker = days_ >= 365 ? " Y" : days_ >= 30 ? " M" : " D"
Dynamic Coloring: Older zones are drawn with stronger fill, while newer ones appear fainter—making it easy to assess significance.
Self-Cleaning Logic: If price invalidates a zone, it’s instantly removed, keeping the chart clean and focused.
🔵 FEATURES
Upper and Lower Zones: Auto-detects valid high/low pivots and plots horizontal zones with ATR-based thickness.
Real-Time Validation: Zones are extended only if price stays outside them—giving precise control zones.
Gradient Fill Intensity: The longer a level survives, the more opaque the fill becomes.
Duration-Based Labeling: Time alive is shown at the root of each zone:
• D – short-term zones
• M – medium-term structure
• Y – long-term legacy levels
Smart Zone Clearing: Zones are deleted automatically once invalidated by price, keeping the display accurate.
Efficient Memory Handling: Keeps only the 10 most recent valid levels per side for optimal performance.
🔵 HOW TO USE
Track durable S/R zones that survived price tests without being breached.
Use longer-lived zones as high-confidence confluence areas for entries or targets.
Observe fill intensity to judge structural importance at a glance .
Layer with volume or momentum tools to confirm bounce or breakout probability.
Ideal for swing traders, structure-based traders, or macro analysis.
🔵 CONCLUSION
Non-Lagging Longevity Zones lets the market speak for itself—by spotlighting levels with proven survival over time. Whether you're trading trend continuation, mean reversion, or structure-based reversals, this tool equips you with an immediate read on what price zones truly matter—and how long they've stood the test of time.
Auto-Length Anchored Multiple EMA (Hour-Based)# Auto-Length Anchored Multiple EMA (Hour-Based)
## Overview
This advanced EMA indicator automatically calculates Exponential Moving Average lengths based on the time elapsed since user-defined anchor dates. Unlike traditional fixed-length EMAs, this indicator dynamically adjusts EMA periods based on actual trading hours, making it ideal for event-based analysis and time-sensitive trading strategies.
## Key Features
### 🎯 **Dual Mode Operation**
- **Auto Mode**: EMA length automatically calculated from anchor date to current time
- **Manual Mode**: Traditional fixed-length EMA calculation
- Switch between modes independently for each EMA
### 📊 **Multiple EMA Support**
- Up to 4 independent EMAs with individual configurations
- Each EMA can have its own anchor date and settings
- Individual enable/disable controls for each EMA
### ⏰ **Smart Time Calculation**
- Accounts for actual trading hours (customizable)
- Weekend exclusion with Saturday trading option (for markets like NSE/BSE)
- Hour multiplier for fine-tuning EMA sensitivity
- Minimum EMA length protection to prevent calculation errors
### 🎨 **Visual Enhancements**
- **Dynamic Fill Colors**: Fill between EMA1 and EMA3 changes color based on price position
- **Customizable Colors**: Individual color settings for each EMA
- **Anchor Visualization**: Optional vertical lines and labels at anchor dates
- **Real-time Table**: Shows current EMA lengths, modes, and values
## Configuration Options
### Trading Session Settings
- **Trading Hours Per Day**: Set your market's trading hours (1-24)
- **Trading Days Per Week**: Configure for different markets (5 for Mon-Fri, 6 for Mon-Sat)
- **Include Saturday**: Enable for markets that trade on Saturday
- **Hour Multiplier**: Fine-tune EMA sensitivity (0.1x to 10x)
### EMA Configuration
- **Anchor Dates**: Set specific start dates for each EMA calculation
- **Manual Lengths**: Override with traditional fixed periods when needed
- **Enable/Disable**: Individual control for each EMA
- **Color Customization**: Personalize appearance for each EMA
### Visual Options
- **Fill Settings**: Toggle and customize fill colors between EMAs
- **Anchor Lines**: Show vertical lines at anchor dates
- **Anchor Labels**: Display formatted anchor date information
- **Length Table**: Real-time display of current EMA parameters
## Use Cases
### 📈 **Event-Based Analysis**
- Anchor EMAs to earnings announcements, policy decisions, or market events
- Track price behavior relative to specific time periods
- Analyze momentum changes from key market catalysts
### 🕐 **Time-Sensitive Trading**
- Perfect for intraday strategies where timing is crucial
- Automatically adjusts to market hours and trading sessions
- Eliminates manual EMA length recalculation
### 🌍 **Multi-Market Support**
- Configurable for different global markets
- Saturday trading support for Asian markets
- Flexible trading hour settings
## Technical Details
### Calculation Method
The indicator calculates trading bars elapsed since anchor date using:
```
Total Trading Bars = (Days Since Anchor × Trading Days Per Week ÷ 7) × Trading Hours Per Day × Hour Multiplier
```
### EMA Formula
Uses standard EMA calculation with dynamically calculated alpha:
```
Alpha = 2 ÷ (Current Length + 1)
EMA = Alpha × Current Price + (1 - Alpha) × Previous EMA
```
### Weekend Handling
- Automatically excludes weekends from calculation
- Optional Saturday inclusion for specific markets
- Accurate trading day counting
## Installation & Setup
1. **Add to Chart**: Apply the indicator to your desired timeframe
2. **Set Anchor Dates**: Configure anchor dates for each EMA you want to use
3. **Adjust Trading Hours**: Set your market's trading session parameters
4. **Customize Appearance**: Choose colors and visual options
5. **Enable Features**: Turn on fills, anchor lines, and information table as needed
## Best Practices
- **Anchor Selection**: Choose significant market events or technical breakouts as anchor points
- **Multiple Timeframes**: Use different anchor dates for short, medium, and long-term analysis
- **Hour Multiplier**: Start with 1.0 and adjust based on market volatility and your trading style
- **Visual Clarity**: Use contrasting colors for different EMAs to improve readability
## Compatibility
- **Pine Script Version**: v6
- **Chart Types**: All chart types supported
- **Timeframes**: Works on all timeframes (optimal on intraday charts)
- **Markets**: Suitable for stocks, forex, crypto, and commodities
## Notes
- Indicator starts calculation from the anchor date forward
- Minimum EMA length prevents calculation errors with very recent anchor dates
- Table display updates in real-time showing current EMA parameters
- Fill colors dynamically change based on price position relative to EMA1
---
*This indicator is perfect for traders who want to combine the power of EMAs with event-driven analysis and precise time-based calculations.*
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
Super MTF Clouds (4x3 Pairs)Overview:
This script is based on Ripster's MTF clouds, which transcends the standard moving average cloud indicator by offering a powerful and deeply customizable Multi-Timeframe (MTF) analysis. Instead of being limited to the moving averages of your current charts from the current timeframe, this tool allows you to project and visualize the trend and key support/resistance zones from up to 4 different timeframes simultaneously. User can input up to 6 different EMA values which will form 3 pairs of EMA clouds, for each of the timeframes.
The primary purpose is to provide traders with immediate confluence. By observing how price interacts with moving average clouds from higher timeframes (e.g., Hourly, Daily, Weekly), you can make more informed decisions on your active trading timeframe (e.g., 10 Minute). It's designed as a complete MTF Cloud toolkit, allowing you to display all necessary MTFs in a single script to build a comprehensive view of the market structure without having to flick to different timeframe to look for cloud positions.
Key features:
Four Independent Multi-Timeframe Slots: Each slot can be assigned any timeframe available on TradingView (e.g., D, W, M, 4H).
Three MA Pairs Per Timeframe: For each timeframe, configure up to three separate MA clouds (e.g., a 9/12 EMA pair, a 20/50 EMA pair, and a 100/200 SMA pair).
Complete Customisation: For every single moving average (24 in total), you can independently control:
MA Type: Choose between EMA or SMA.
Length: Any period you require.
Line Color: Full colour selection.
Line Thickness: Adjust the visual weight of each line.
Cloud Control: For every pair (12 in total), you can set the fill colour and transparency.
How To Use This Script:
This tool is best used for confirmation and context. Here are some practical strategies that one can adopt:
Trend Confluence: Before taking a trade based on a signal on your current timeframe, glance at the higher timeframe clouds. If you see a buy signal on the 15-minute chart and the price is currently trading above a thick, bullish Daily cloud, the probability of that trade succeeding is significantly higher. Conversely, shorting into strong HTF support is a low-probability trade.
Dynamic Support & Resistance: The edges of the higher timeframe clouds often act as powerful, dynamic levels of support and resistance. A pullback to the 4-Hour 50 EMA on your 15-minute chart can be a prime area to look for entries in the direction of the larger trend.
Gauging Market Regimes: Use the toggles in the settings to quickly switch between different views. You can have a "risk-on" view with short-term clouds and a "macro" view with weekly and monthly clouds. This helps you adapt your trading style to the current market conditions.
Key Settings:
1. Global Setting
Source For All MAs: This determines the price data point used for every single moving average calculation.
Default: hl2 (an average of the High and Low of each bar). This gives a smooth midpoint price.
Options: You can change this to Close (the most common method), Open, High, Low, or ohlc4 (an average of the open, high, low, and close), among others.
Recommendation: For most standard trend analysis, the default hl2 is the common choice.
2. The Timeframe Group Structure
The rest of the settings are organized into four identical, collapsible groups: "Timeframe 1 Settings" through "Timeframe 4 Settings". Each group acts as a self-contained control panel for one multi-timeframe view.
Within each timeframe group, you have two master controls:
Enable Timeframe: This is the main power switch for the entire group. Uncheck this box to instantly hide all three clouds and lines associated with this timeframe. This is perfect for quickly decluttering your chart or focusing on a different set of analyses.
Timeframe: This dropdown menu is the heart of the MTF feature. Here, you select the higher timeframe you want to analyse (e.g., 1D for Daily, 1W for Weekly, 4H for 4-Hour). All calculations for the three pairs within this group will be based on the timeframe you select here.
3. Pair-Specific Controls
Inside each timeframe group, there are three sections for "Pair 1", "Pair 2", and "Pair 3". These control each individual moving average cloud.
Enable Pair: Just like the master switch for the timeframe, this checkbox turns a single cloud and its two MA lines on or off.
For each pair, the settings are further broken down:
Moving Average Lines (A and B): These two rows control the two moving averages that form the cloud. 'A' is typically used for the shorter-period MA and 'B' for the longer-period one.
Type (A/B): A dropdown menu to select either EMA (Exponential Moving Average) or SMA (Simple Moving Average). EMAs react more quickly to recent price changes, while SMAs are smoother and react more slowly.
Length (A/B): The lookback period for the moving average (e.g., 21, 50, 200).
Color (A/B): Sets the specific colour of the MA line itself on your chart.
Cloud Fill Settings
Fill Color: This controls the colour of the shaded area (the "cloud") between the two moving average lines. For a consistent look, you can set this to the same colour as your shorter MA line.
Transparency: Controls how see-through the cloud is, on a scale of 0 to 100. 0 is a solid, opaque colour, while 100 is completely invisible. The default of 85 provides a light, "cloud-like" appearance that doesn't obscure the price action.
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If anything is not clear please let me know!
Gorgo's Hybrid Oscillator STrategy**Indicator Name:** Gorgo's Hybrid Oscillator STrategy (G.H.O.S.T.)
**Purpose:**
The Gorgo's Hybrid Oscillator STrategy (G.H.O.S.T.) is a multi-component technical analysis tool designed to identify overbought and oversold market conditions, assess trend strength, and signal potential buy and sell opportunities. By combining elements from RSI, Ultimate Oscillator, Stochastic CCI, and ADX, this custom indicator provides a comprehensive view of momentum, trend intensity, and volume context to enhance decision-making.
---
**Components and Logic:**
1. **RSI (Relative Strength Index):**
* Calculated using a customizable period (default: 14) and based on the hlc3 price source.
* Measures recent price changes to evaluate overbought/oversold conditions.
* Incorporated in the final oscillator average.
2. **Ultimate Oscillator:**
* Combines three timeframes (7, 14, 28 by default) to smooth out price movements.
* Uses true range and buying pressure for multi-frame momentum analysis.
* Averaged together with RSI to create the main oscillator signal.
3. **Stochastic CCI:**
* Applies a stochastic process to the Commodity Channel Index (CCI).
* Smooths the %K and %D lines (default: 3 each) to detect subtle reversals.
* Generates oversold (<35) and overbought (>69) signals, plotted as yellow circles.
4. **ADX + DI (Average Directional Index):**
* Determines trend strength using ADX and directional movement indicators (DI).
* ADX threshold is set at 24 by default to filter weak trends.
* Colored histogram columns:
* Green: Strong bullish trend.
* Red: Strong bearish trend.
* Gray: Weak/no trend.
5. **Volume Analysis:**
* Calculates a 9-period SMA of volume.
* Detects significant volume spikes (2.7× the average by default) to validate breakouts or fakeouts.
6. **Oscillator Output ("osc") and Levels:**
* The main plotted oscillator line is the average of the RSI and Ultimate Oscillator.
* Important horizontal lines:
* Overbought (69.0)
* Oversold (35.0)
* Midline (52.0): Neutral reference point.
* ADX threshold line (24.0)
---
**Signals:**
1. **Buy Signal Conditions:**
* Close is less than or equal to open (candle is red).
* Oscillator is decreasing and below oversold level.
* Stochastic CCI is below midline.
* Volume is above average, or excessive volume with oscillator falling below 40.
* ADX confirms trend presence (either above 15 or meeting threshold).
2. **Sell Signal Conditions:**
* ADX increasing and confirming trend.
* Oscillator is increasing and above overbought level.
* Stochastic CCI is above midline.
* Volume is above average, or very high with oscillator above 60.
3. **Visual Feedback:**
* Yellow dots highlight oversold/overbought Stochastic CCI.
* Oscillator line in cyan.
* Background colors:
* Light red for buy signals.
* White for sell signals.
4. **Alerts:**
* Built-in `alertcondition()` calls allow automated alerts for buy and sell events.
---
**Usage Guide:**
* **Best Use Cases:** Trend-following and reversal strategies on any timeframe.
* **Avoid Using Alone:** Use G.H.O.S.T. in conjunction with price action, support/resistance, and other confluence tools.
* **Customization:** All thresholds, periods, and volumes are user-editable from the settings panel.
---
**Interpretation Summary:**
G.H.O.S.T. excels at filtering out noise by combining different oscillators and volume signals to offer contextually valid entries and exits. A bullish (buy) signal typically suggests a market under pressure but potentially bottoming out, while a bearish (sell) signal highlights likely exhaustion after a strong upward push.
This hybrid approach makes the G.H.O.S.T. a reliable ally in volatile or choppy conditions where single-indicator strategies might fail.
Session Range ProjectionsSession Range Projections
Purpose & Concept:
Session Range Projections is a comprehensive trading tool that identifies and analyzes price ranges during user-defined time periods. The indicator visualizes high-probability reversal zones and profit targets by projecting Fibonacci levels from custom session ranges, making it ideal for traders who focus on time-based market structure analysis.
Key Features & Calculations:
1. Custom Time Range Analysis
- Define any time period for range calculation - from traditional sessions (Asian, London, NY) to custom periods like opening ranges, hourly ranges, or 4-hour blocks
- Automatically captures the highest and lowest prices within your specified timeframe
- Supports multiple timezone selections for global market analysis
- Flexible enough for intraday scalping ranges or longer-term swing trading setups
2. Premium & Discount Zones
- Automatically divides the range into premium (above 50%) and discount (below 50%) zones
- Visual differentiation helps identify institutional buying and selling areas
- Color-coded boxes clearly mark these critical price zones
3. Optimal Trade Entry (OTE) Zones
- Highlights the 79-89% retracement zone in premium territory
- Highlights the 11-21% retracement zone in discount territory
- These zones represent high-probability reversal areas based on institutional order flow concepts
4. Fibonacci Projections
- Projects 11 customizable Fibonacci extension levels from the range extremes
- Levels extend both above and below the range for symmetrical analysis
- Each level can be individually toggled and color-customized
- Default levels include common retracement ratios: -0.5, -1.0, -2.0, -2.33, -2.5, -3.0, -4.0, -4.5, -6.0, -7.0, -8.0
How to Use:
Set Your Time Range: Input your desired session start and end times (24-hour format)
Select Timezone: Choose the appropriate timezone for your trading session
Customize Display: Toggle various visual elements based on your preferences
Monitor Price Action: Watch for reactions at projected levels and OTE zones
Set Alerts: Configure sweep alerts for when price breaks above/below range extremes
Input Parameters Explained:
Time Range Settings
Range Start/End Hour & Minute: Define your analysis period
Time Zone: Ensure accurate session timing across different markets
Visual Settings
Range Box: Toggle the premium/discount zone visualization
Horizontal Lines: Customize high/low line appearance
Internal Range Levels: Show/hide equilibrium and OTE zones
Labels: Configure text display for key levels
Fibonacci Projections: Enable/disable extension levels
Display Settings
Historical Ranges: Show up to 10 previous session ranges
Alert Type: Choose between high sweep, low sweep, or both
Trading Applications:
Session-Based Trading: Analyze specific market sessions (Asian, London, New York, opening ranges, hourly ranges)
Reversal Trading: Identify high-probability reversal zones at OTE levels
Breakout/Reversal Trading: Monitor range breaks/reversals with built-in sweep alerts
Risk Management: Use Fibonacci projections as profit targets or rejection areas
Multi-Timeframe Analysis: Apply to any timeframe for various trading styles
Important Notes:
This indicator is for educational purposes only and should not be considered financial advice
Past performance does not guarantee future results
Always use proper risk management when trading
The indicator automatically manages historical data to maintain chart performance
Multi-Timeline 1.0Multi-TimeLines 1.0 - Comprehensive Description
WHAT IT DOES:
This indicator creates dynamic horizontal support/resistance lines based on opening prices captured at user-defined New York times. Unlike static horizontal lines, these levels automatically appear and disappear based on sophisticated session logic, providing traders with time-sensitive reference levels that adapt to market sessions.
HOW IT WORKS - TECHNICAL IMPLEMENTATION:
1.
Timezone Conversion Engine:
The script uses Pine Script's "America/New_York" timezone functions to ensure all time calculations are based on NY time, regardless of the user's chart timezone. This eliminates confusion and provides consistent behavior across global markets.
2.
Dual-Category Time Classification System:
The indicator employs a unique two-category classification system:
Category A (16:00-23:59 NY): Evening times that extend overnight until next day 15:59 NY
Category B (00:00-15:59 NY): Day times that extend until same day 15:59 NY
This classification handles the complex logic of overnight sessions and prevents lines from incorrectly resetting at midnight for evening times.
3. Price Capture Mechanism:
Uses precise time-hit detection with backup systems for edge cases (especially midnight 00:00). When a specified time occurs, the script captures the bar's opening price and stores it in persistent variables using Pine Script's var declarations.
4. Session-Aware Display Logic:
Lines only appear during their designated "display windows" - periods when the captured price level is relevant. The script uses conditional plotting with plot.style_linebr to create clean breaks when lines are inactive.
5. Smart Reset System:
Different reset behaviors based on time classification:
Category A times persist across midnight (for overnight analysis)
Category B times reset on day changes (except 00:00 which captures AT day change)
Automatic cleanup when display windows close
ORIGINALITY & UNIQUE FEATURES:
1. Overnight Session Handling:
Unlike basic horizontal line tools, this script properly handles overnight spans for evening times, making it invaluable for analyzing gaps and overnight price action.
2. Automatic Session Management:
No manual line drawing required - the script automatically manages when lines appear/disappear based on NY market sessions (15:59 close, 18:00 after-hours start).
3. Time-Window Display Logic:
Lines only show during relevant periods, reducing chart clutter and focusing attention on currently active levels.
TRADING CONCEPTS & APPLICATIONS:
1. Session-Based Analysis:
Capture opening prices at key session times:
00:00 NY: Sydney/Asian session start
03:00 NY: London pre-market
08:00 NY: London session open
09:30 NY: NYSE opening bell
18:00 NY: After-hours start
2. Gap Analysis:
Evening times (20:00-23:59) that extend overnight are particularly useful for:
Identifying potential gap-fill levels
Tracking overnight high/low breaks
Setting reference points for next-day trading
3. Support/Resistance Framework:
Opening prices at significant times often act as:
Intraday support/resistance levels
Reference points for breakout/breakdown analysis
Pivot levels for mean reversion strategies
HOW TO USE:
1. Time Input:
Enter times in "HH:MM" format using 24-hour NY time:
"09:30" for NYSE open
"15:30" for late-day reference
"20:00" for evening level (extends overnight)
2. Line Behavior:
Blue/Green/Cyan/Red lines: Your custom times
Yellow line: After-hours day open (18:00 NY start)
Lines appear with breaks during inactive periods
3. Strategic Setup:
Use 2-3 key session times for your trading style
Combine morning times (immediate reference) with evening times (overnight analysis)
Toggle after-hours line based on your market focus
CALCULATION METHOD:
The script uses direct opening price capture (no smoothing or averaging) at precise time hits, ensuring the most accurate representation of actual market levels at specified times. This raw price approach maintains the integrity of actual market opening prices rather than manipulated or calculated values.
This method is particularly effective because opening prices at significant times often represent institutional order flow and can act as magnetic levels throughout subsequent sessions.
ATR-InfoWHAT IT SHOWS
- ATR (): Average True Range of the chosen timeframe, printed with the instrument’s native tick precision (format.mintick).
- ATR % PRICE: ATR divided by the latest close, multiplied by 100 – the range as a percentage of current price.
- LEN / TF: The ATR length and timeframe you selected (shown in small print).
INPUTS
- ATR Length (default 14)
- ATR Timeframe (for example 60, D, W)
- Design settings: table position, font size, colours, border
EXAMPLES
BTC-USD: price 67 800, ATR 2 450, ATR % 3.6
NQ E-Mini: price 18 230, ATR 355, ATR % 1.9
CL WTI: price 76.40, ATR 2.10, ATR % 2.8
EUR-USD: price 1.0860, ATR 0.0075, ATR % 0.69
USE CASES
Volatility-adjusted stops: place your stop roughly one ATR beyond the entry price.
Position sizing: money at risk divided by ATR gives the number of contracts or coins.
Market selection: trade assets only when their ATR % sits in your preferred range.
Strategy filter: trigger entries or exits only when ATR % crosses a chosen threshold.
LIMITS
ATR is descriptive; it does not predict future moves.
Illiquid symbols may show exaggerated ATR spikes.
ATR % ignores differing session lengths (24/7 crypto versus exchange-traded hours).
Z-Score Adaptive Connors RSIZ-Score Adaptive Connors RSI blends the classic three-component Connors RSI (RSI, Up/Down streak RSI, and Percentile Rank of 1-bar ROC) with a dynamic z-score filter that distinguishes trending vs. mean-reverting market regimes.
When the indicator detects an extreme deviation (|z-score| > threshold) , it switches to “trending” mode and tightens entry thresholds for capturing momentum. When markets are in a more neutral regime, it reverts to wider thresholds, hunting for overbought/oversold reversals.
Key Features
Connors RSI Core: Combines price momentum, streak measurements, and velocity for a robust baseline oscillator. Z-Score Regime Filter: Computes the z-score of the Connors RSI over a lookback window to adapt your trading style to trending vs. reverting environments.
Dynamic Thresholds: Separate user-configurable thresholds for trending (“tight” entries) and mean-reverting (“wide” entries) scenarios.
Inputs & Parameters
Connors RSI Settings
RSI Source: Price series for RSI calculation (default: Close)
RSI Length: Period for price‐change RSI (default: 24)
Up/Down Length: Period for streak RSI (default: 20)
ROC Length: Period for percentile‐rank of 1-bar return (default: 75)
Z-Score Filter
Lookback: Number of bars to compute mean and standard deviation of Connors RSI (default: 14)
Threshold: Minimum |z-score| to enter “trending” mode (default: 1.5)
Entry Thresholds
Trending Long/Short: Upper and lower RSI Thresholds when trending
Reverting Long/Short: Upper and lower RSI Thresholds when reverting
Institutional Volume Profile# Institutional Volume Profile (IVP) - Advanced Volume Analysis Indicator
## Overview
The Institutional Volume Profile (IVP) is a sophisticated technical analysis tool that combines traditional volume profile analysis with institutional volume detection algorithms. This indicator helps traders identify key price levels where significant institutional activity has occurred, providing insights into market structure and potential support/resistance zones.
## Key Features
### 🎯 Volume Profile Analysis
- **Point of Control (POC)**: Identifies the price level with the highest volume activity
- **Value Area**: Highlights the price range containing a specified percentage (default 70%) of total volume
- **Multi-Row Distribution**: Displays volume distribution across 10-50 price levels for detailed analysis
- **Customizable Period**: Analyze volume profiles over 10-500 bars
### 🏛️ Institutional Volume Detection
- **Pocket Pivot Volume (PPV)**: Detects bullish institutional buying when up-volume exceeds recent down-volume peaks
- **Pivot Negative Volume (PNV)**: Identifies bearish institutional selling when down-volume exceeds recent up-volume peaks
- **Accumulation Detection**: Spots potential accumulation phases with high volume and narrow price ranges
- **Distribution Analysis**: Identifies distribution patterns with high volume but minimal price movement
### 🎨 Visual Customization Options
- **Multiple Color Schemes**: Heat Map, Institutional, Monochrome, and Rainbow themes
- **Bar Styles**: Solid, Gradient, Outlined, and 3D Effect rendering
- **Volume Intensity Display**: Visual intensity based on volume magnitude
- **Flexible Positioning**: Left or right side profile placement
- **Current Price Highlighting**: Real-time price level indication
### 📊 Advanced Visual Features
- **Volume Labels**: Display volume amounts at key price levels
- **Gradient Effects**: Multi-step gradient rendering for enhanced visibility
- **3D Styling**: Shadow effects for professional appearance
- **Opacity Control**: Adjustable transparency (10-100%)
- **Border Customization**: Configurable border width and styling
## How It Works
### Volume Distribution Algorithm
The indicator analyzes each bar within the specified period and distributes its volume proportionally across the price levels it touches. This creates an accurate representation of where trading activity has been concentrated.
### Institutional Detection Logic
- **PPV Trigger**: Current up-bar volume > highest down-volume in lookback period + above volume MA
- **PNV Trigger**: Current down-bar volume > highest up-volume in lookback period + above volume MA
- **Accumulation**: High volume + narrow range + bullish close
- **Distribution**: Very high volume + minimal price movement
### Value Area Calculation
Starting from the POC, the algorithm expands both upward and downward, adding volume until reaching the specified percentage of total volume (default 70%).
## Configuration Parameters
### Profile Settings
- **Profile Period**: 10-500 bars (default: 50)
- **Number of Rows**: 10-50 levels (default: 24)
- **Profile Width**: 10-100% of screen (default: 30%)
- **Value Area %**: 50-90% (default: 70%)
### Institutional Analysis
- **PPV Lookback Days**: 5-20 periods (default: 10)
- **Volume MA Length**: 10-200 periods (default: 50)
- **Institutional Threshold**: 1.0-2.0x multiplier (default: 1.2)
### Visual Controls
- **Bar Style**: Solid, Gradient, Outlined, 3D Effect
- **Color Scheme**: Heat Map, Institutional, Monochrome, Rainbow
- **Profile Position**: Left or Right side
- **Opacity**: 10-100%
- **Show Labels**: Volume amount display toggle
## Interpretation Guide
### Volume Profile Elements
- **Thick Horizontal Bars**: High volume nodes (strong support/resistance)
- **Thin Horizontal Bars**: Low volume nodes (weak levels)
- **White Line (POC)**: Strongest support/resistance level
- **Blue Highlighted Area**: Value Area (fair value zone)
### Institutional Signals
- **Blue Triangles (PPV)**: Bullish institutional buying detected
- **Orange Triangles (PNV)**: Bearish institutional selling detected
- **Color-Coded Bars**: Different colors indicate institutional activity types
### Color Scheme Meanings
- **Heat Map**: Red (high volume) → Orange → Yellow → Gray (low volume)
- **Institutional**: Blue (PPV), Orange (PNV), Aqua (Accumulation), Yellow (Distribution)
- **Monochrome**: Grayscale intensity based on volume
- **Rainbow**: Color-coded by price level position
## Trading Applications
### Support and Resistance
- POC acts as dynamic support/resistance
- High volume nodes indicate strong price levels
- Low volume areas suggest potential breakout zones
### Institutional Activity
- PPV above Value Area: Strong bullish signal
- PNV below Value Area: Strong bearish signal
- Accumulation patterns: Potential upward breakouts
- Distribution patterns: Potential downward pressure
### Market Structure Analysis
- Value Area defines fair value range
- Profile shape indicates market sentiment
- Volume gaps suggest potential price targets
## Alert Conditions
- PPV Detection at current price level
- PNV Detection at current price level
- PPV above Value Area (strong bullish)
- PNV below Value Area (strong bearish)
## Best Practices
1. Use multiple timeframes for confirmation
2. Combine with price action analysis
3. Pay attention to volume context (above/below average)
4. Monitor institutional signals near key levels
5. Consider overall market conditions
## Technical Notes
- Maximum 500 boxes and 100 labels for optimal performance
- Real-time calculations update on each bar close
- Historical analysis uses complete bar data
- Compatible with all TradingView chart types and timeframes
---
*This indicator is designed for educational and informational purposes. Always combine with other analysis methods and risk management strategies.*
Bias Ratio-ETH-3H @CTTC5108Most of the code of this strategy should be my own original.
This Ethereum 3-hour time cycle strategy can be traced back to February 24, 2023. Although the profit and winning rate are not high, it is still relatively stable.
This strategy uses the deviation rate to enter the market. Invest 10% of the principal each time.
The limit start time adopts a rolling design (should be original).
Real-time retracement and maximum retracement are accurately calculated (should be original).
Adopt segmented stop profit (optional) design.
Open source for learning and other use.
Bear Market Probability Model# Bear Market Probability Model: A Multi-Factor Risk Assessment Framework
The Bear Market Probability Model represents a comprehensive quantitative framework for assessing systemic market risk through the integration of 13 distinct risk factors across four analytical categories: macroeconomic indicators, technical analysis factors, market sentiment measures, and market breadth metrics. This indicator synthesizes established financial research methodologies to provide real-time probabilistic assessments of impending bear market conditions, offering institutional-grade risk management capabilities to retail and professional traders alike.
## Theoretical Foundation
### Historical Context of Bear Market Prediction
Bear market prediction has been a central focus of financial research since the seminal work of Dow (1901) and the subsequent development of technical analysis theory. The challenge of predicting market downturns gained renewed academic attention following the market crashes of 1929, 1987, 2000, and 2008, leading to the development of sophisticated multi-factor models.
Fama and French (1989) demonstrated that certain financial variables possess predictive power for stock returns, particularly during market stress periods. Their three-factor model laid the groundwork for multi-dimensional risk assessment, which this indicator extends through the incorporation of real-time market microstructure data.
### Methodological Framework
The model employs a weighted composite scoring methodology based on the theoretical framework established by Campbell and Shiller (1998) for market valuation assessment, extended through the incorporation of high-frequency sentiment and technical indicators as proposed by Baker and Wurgler (2006) in their seminal work on investor sentiment.
The mathematical foundation follows the general form:
Bear Market Probability = Σ(Wi × Ci) / ΣWi × 100
Where:
- Wi = Category weight (i = 1,2,3,4)
- Ci = Normalized category score
- Categories: Macroeconomic, Technical, Sentiment, Breadth
## Component Analysis
### 1. Macroeconomic Risk Factors
#### Yield Curve Analysis
The inclusion of yield curve inversion as a primary predictor follows extensive research by Estrella and Mishkin (1998), who demonstrated that the term spread between 3-month and 10-year Treasury securities has historically preceded all major recessions since 1969. The model incorporates both the 2Y-10Y and 3M-10Y spreads to capture different aspects of monetary policy expectations.
Implementation:
- 2Y-10Y Spread: Captures market expectations of monetary policy trajectory
- 3M-10Y Spread: Traditional recession predictor with 12-18 month lead time
Scientific Basis: Harvey (1988) and subsequent research by Ang, Piazzesi, and Wei (2006) established the theoretical foundation linking yield curve inversions to economic contractions through the expectations hypothesis of the term structure.
#### Credit Risk Premium Assessment
High-yield credit spreads serve as a real-time gauge of systemic risk, following the methodology established by Gilchrist and Zakrajšek (2012) in their excess bond premium research. The model incorporates the ICE BofA High Yield Master II Option-Adjusted Spread as a proxy for credit market stress.
Threshold Calibration:
- Normal conditions: < 350 basis points
- Elevated risk: 350-500 basis points
- Severe stress: > 500 basis points
#### Currency and Commodity Stress Indicators
The US Dollar Index (DXY) momentum serves as a risk-off indicator, while the Gold-to-Oil ratio captures commodity market stress dynamics. This approach follows the methodology of Akram (2009) and Beckmann, Berger, and Czudaj (2015) in analyzing commodity-currency relationships during market stress.
### 2. Technical Analysis Factors
#### Multi-Timeframe Moving Average Analysis
The technical component incorporates the well-established moving average convergence methodology, drawing from the work of Brock, Lakonishok, and LeBaron (1992), who provided empirical evidence for the profitability of technical trading rules.
Implementation:
- Price relative to 50-day and 200-day simple moving averages
- Moving average convergence/divergence analysis
- Multi-timeframe MACD assessment (daily and weekly)
#### Momentum and Volatility Analysis
The model integrates Relative Strength Index (RSI) analysis following Wilder's (1978) original methodology, combined with maximum drawdown analysis based on the work of Magdon-Ismail and Atiya (2004) on optimal drawdown measurement.
### 3. Market Sentiment Factors
#### Volatility Index Analysis
The VIX component follows the established research of Whaley (2009) and subsequent work by Bekaert and Hoerova (2014) on VIX as a predictor of market stress. The model incorporates both absolute VIX levels and relative VIX spikes compared to the 20-day moving average.
Calibration:
- Low volatility: VIX < 20
- Elevated concern: VIX 20-25
- High fear: VIX > 25
- Panic conditions: VIX > 30
#### Put-Call Ratio Analysis
Options flow analysis through put-call ratios provides insight into sophisticated investor positioning, following the methodology established by Pan and Poteshman (2006) in their analysis of informed trading in options markets.
### 4. Market Breadth Factors
#### Advance-Decline Analysis
Market breadth assessment follows the classic work of Fosback (1976) and subsequent research by Brown and Cliff (2004) on market breadth as a predictor of future returns.
Components:
- Daily advance-decline ratio
- Advance-decline line momentum
- McClellan Oscillator (Ema19 - Ema39 of A-D difference)
#### New Highs-New Lows Analysis
The new highs-new lows ratio serves as a market leadership indicator, based on the research of Zweig (1986) and validated in academic literature by Zarowin (1990).
## Dynamic Threshold Methodology
The model incorporates adaptive thresholds based on rolling volatility and trend analysis, following the methodology established by Pagan and Sossounov (2003) for business cycle dating. This approach allows the model to adjust sensitivity based on prevailing market conditions.
Dynamic Threshold Calculation:
- Warning Level: Base threshold ± (Volatility × 1.0)
- Danger Level: Base threshold ± (Volatility × 1.5)
- Bounds: ±10-20 points from base threshold
## Professional Implementation
### Institutional Usage Patterns
Professional risk managers typically employ multi-factor bear market models in several contexts:
#### 1. Portfolio Risk Management
- Tactical Asset Allocation: Reducing equity exposure when probability exceeds 60-70%
- Hedging Strategies: Implementing protective puts or VIX calls when warning thresholds are breached
- Sector Rotation: Shifting from growth to defensive sectors during elevated risk periods
#### 2. Risk Budgeting
- Value-at-Risk Adjustment: Incorporating bear market probability into VaR calculations
- Stress Testing: Using probability levels to calibrate stress test scenarios
- Capital Requirements: Adjusting regulatory capital based on systemic risk assessment
#### 3. Client Communication
- Risk Reporting: Quantifying market risk for client presentations
- Investment Committee Decisions: Providing objective risk metrics for strategic decisions
- Performance Attribution: Explaining defensive positioning during market stress
### Implementation Framework
Professional traders typically implement such models through:
#### Signal Hierarchy:
1. Probability < 30%: Normal risk positioning
2. Probability 30-50%: Increased hedging, reduced leverage
3. Probability 50-70%: Defensive positioning, cash building
4. Probability > 70%: Maximum defensive posture, short exposure consideration
#### Risk Management Integration:
- Position Sizing: Inverse relationship between probability and position size
- Stop-Loss Adjustment: Tighter stops during elevated risk periods
- Correlation Monitoring: Increased attention to cross-asset correlations
## Strengths and Advantages
### 1. Comprehensive Coverage
The model's primary strength lies in its multi-dimensional approach, avoiding the single-factor bias that has historically plagued market timing models. By incorporating macroeconomic, technical, sentiment, and breadth factors, the model provides robust risk assessment across different market regimes.
### 2. Dynamic Adaptability
The adaptive threshold mechanism allows the model to adjust sensitivity based on prevailing volatility conditions, reducing false signals during low-volatility periods and maintaining sensitivity during high-volatility regimes.
### 3. Real-Time Processing
Unlike traditional academic models that rely on monthly or quarterly data, this indicator processes daily market data, providing timely risk assessment for active portfolio management.
### 4. Transparency and Interpretability
The component-based structure allows users to understand which factors are driving risk assessment, enabling informed decision-making about model signals.
### 5. Historical Validation
Each component has been validated in academic literature, providing theoretical foundation for the model's predictive power.
## Limitations and Weaknesses
### 1. Data Dependencies
The model's effectiveness depends heavily on the availability and quality of real-time economic data. Federal Reserve Economic Data (FRED) updates may have lags that could impact model responsiveness during rapidly evolving market conditions.
### 2. Regime Change Sensitivity
Like most quantitative models, the indicator may struggle during unprecedented market conditions or structural regime changes where historical relationships break down (Taleb, 2007).
### 3. False Signal Risk
Multi-factor models inherently face the challenge of balancing sensitivity with specificity. The model may generate false positive signals during normal market volatility periods.
### 4. Currency and Geographic Bias
The model focuses primarily on US market indicators, potentially limiting its effectiveness for global portfolio management or non-USD denominated assets.
### 5. Correlation Breakdown
During extreme market stress, correlations between risk factors may increase dramatically, reducing the model's diversification benefits (Forbes and Rigobon, 2002).
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Bitcoin Open Interest [SAKANE]Bitcoin Open Interest
— Unveiling the True Flow of Capital
PurposeVisualize and compare Bitcoin open interest (OI) from CME and Binance, the leading derivatives exchanges, in a single intuitive chart, providing traders with clear insights into crypto market capital dynamics.
Background & MotivationIn the 24/7 crypto market, price movements alone reveal only part of the story. Open interest (OI)—the total outstanding futures contracts—offers critical clues to the market’s next move. Yet, accessing and interpreting OI data is challenging:
CME Constraints: Commitment of Traders (COT) reports are weekly, and standalone BTC1! or BTC2! OI is noisy due to contract rollovers, obscuring true OI changes.
Existing Tool Limitations: Most OI indicators are fixed to either USD or BTC, limiting flexible analysis.
This indicator overcomes these hurdles, enabling seamless comparison of CME and Binance OI to track the market’s “capital center of gravity” in real time.
Key Features
Synthetic CME OI: Combines BTC1! and BTC2! to deliver high-accuracy OI, eliminating rollover noise.
Multi-Timeframe Analysis: Displays daily CME OI as pseudo-candlestick (OHLC) on any timeframe (e.g., 4H), allowing intuitive capital flow tracking across timeframes.
CME/Binance One-Click Toggle: Instantly compare institutional-driven CME and retail-driven Binance OI.
USD/BTC Flexibility: Switch between BTC (real demand) and USD (margin) perspectives for OI analysis.
Robust Design: Concise, global-scope code ensures stability and adaptability to TradingView updates.
Insights & Use Cases
Holistic Market Sentiment: Analyze capital flows by region and exchange for a multidimensional view.
Signal Detection: E.g., a sharp drop in CME OI during a sell-off may signal institutional withdrawal.
Retail Trends: A surge in Binance OI suggests retail-driven inflows.
Event-Driven Insights: E.g., during a hypothetical April 2025 “Trump Tariff Shock,” instantly identify which exchange drives capital shifts.
Unique ValueUnlike price-centric indicators, this tool focuses on capital flow (OI). It’s the only indicator offering one-click multi-timeframe and multi-exchange OI comparison, empowering traders to uncover the market’s “true intent” and gain a strategic edge.
ConclusionBitcoin Open Interest makes the market’s hidden capital movements accessible to all. By capturing market dynamics and pinpointing the “leading forces” during events, it sets a new standard for traders seeking a revolutionary perspective.
