Intrinsic Value AnalyzerThe Intrinsic Value Analyzer is an all-in-one valuation tool that automatically calculates the fair value of a stock using industry-standard valuation techniques. It estimates intrinsic value through Discounted Cash Flow (DCF), Enterprise Value to Revenue (EV/REV), Enterprise Value to EBITDA (EV/EBITDA), and Price to Earnings (P/EPS). The model features adjustable parameters and a built-in alert system that notifies investors in real time when valuation multiples reach predefined thresholds. It also includes a comprehensive, color-coded table that compares the company’s historical average growth rates, valuation multiples, and financial ratios with the most recent values, helping investors quickly assess how current values align with historical averages.
The model calculates the historical Compounded Annual Growth Rates (CAGR) and average valuation multiples over the selected Lookback Period. It then projects Revenue, Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA), Earnings per Share (EPS), and Free Cash Flow (FCF) for the selected Forecast Period and discounts their future values back to the present using the Weighted Average Cost of Capital (WACC) or the Cost of Equity. By default, the model automatically applies the historical averages displayed in the table as the growth forecasts and target multiples. These assumptions can be modified in the menu by entering custom REV-G, EBITDA-G, EPS-G, and FCF-G growth forecasts, as well as EV/REV, EV/EBITDA, and P/EPS target multiples. When new input values are entered, the model recalculates the fair value in real time, allowing users to see how changes in these assumptions affect the company’s fair value.
DCF = (Sum of (FCF × (1 + FCF-G) ^ t ÷ (1 + WACC) ^ t) for each year t until Forecast Period + ((FCF × (1 + FCF-G) ^ Forecast Period × (1 + LT Growth)) ÷ ((WACC - LT Growth) × (1 + WACC) ^ Forecast Period)) + Cash - Debt - Preferred Equity - Minority Interest) ÷ Shares Outstanding
EV/REV = ((Revenue × (1 + REV-G) ^ Forecast Period × EV/REV Target) ÷ (1 + WACC) ^ Forecast Period + Cash - Debt - Preferred Equity - Minority Interest) ÷ Shares Outstanding
EV/EBITDA = ((EBITDA × (1 + EBITDA-G) ^ Forecast Period × EV/EBITDA Target) ÷ (1 + WACC) ^ Forecast Period + Cash - Debt - Preferred Equity - Minority Interest) ÷ Shares Outstanding
P/EPS = (EPS × (1 + EPS-G) ^ Forecast Period × P/EPS Target) ÷ (1 + Cost of Equity) ^ Forecast Period
The discounted one-year average analyst price target (1Y PT) is also displayed alongside the valuation labels to provide an overview of consensus estimates. For the DCF model, the terminal long-term FCF growth rate (LT Growth) is based on the selected country to reflect expected long-term nominal GDP growth and can be modified in the menu. For metrics involving FCF, users can choose between reported FCF, calculated as Cash From Operations (CFO) - Capital Expenditures (CAPEX), or standardized FCF, calculated as Earnings Before Interest and Taxes (EBIT) × (1 - Average Tax Rate) + Depreciation and Amortization - Change in Net Working Capital - CAPEX. Historical average values displayed in the left column of the table are based on Fiscal Year (FY) data, while the latest values in the right column use the most recent Trailing Twelve Month (TTM) or Fiscal Quarter (FQ) data. The indicator displays color-coded price labels for each fair value estimate, showing the percentage upside or downside from the current price. Green indicates undervaluation, while red indicates overvaluation. The table follows a separate color logic:
REV-G, EBITDA-G, EPS-G, FCF-G = Green indicates positive annual growth when the CAGR is positive. Red indicates negative annual growth when the CAGR is negative.
EV/REV = Green indicates undervaluation when EV/REV ÷ REV-G is below 1. Red indicates overvaluation when EV/REV ÷ REV-G is above 2. Gray indicates fair value.
EV/EBITDA = Green indicates undervaluation when EV/EBITDA ÷ EBITDA-G is below 1. Red indicates overvaluation when EV/EBITDA ÷ EBITDA-G is above 2. Gray indicates fair value.
P/EPS = Green indicates undervaluation when P/EPS ÷ EPS-G is below 1. Red indicates overvaluation when P/EPS ÷ EPS-G is above 2. Gray indicates fair value.
EBITDA% = Green indicates profitable operations when the EBITDA margin is positive. Red indicates unprofitable operations when the EBITDA margin is negative.
FCF% = Green indicates strong cash conversion when FCF/EBITDA > 50%. Red indicates unsustainable FCF when FCF/EBITDA is negative. Gray indicates normal cash conversion.
ROIC = Green indicates value creation when ROIC > WACC. Red indicates value destruction when ROIC is negative. Gray indicates positive but insufficient returns.
ND/EBITDA = Green indicates low leverage when ND/EBITDA is below 1. Red indicates high leverage when ND/EBITDA is above 3. Gray indicates moderate leverage.
YIELD = Green indicates positive shareholder return when Shareholder Yield > 1%. Red indicates negative shareholder return when Shareholder Yield < -1%.
The Return on Invested Capital (ROIC) is calculated as EBIT × (1 - Average Tax Rate) ÷ (Average Debt + Average Equity - Average Cash). Shareholder Yield (YIELD) is calculated as the CAGR of Dividend Yield - Change in Shares Outstanding. The Weighted Average Cost of Capital (WACC) is displayed at the top left of the table and is derived from the current Market Cap (MC), Debt, Cost of Equity, and Cost of Debt. The Cost of Equity is calculated using the Equity Beta, Index Return, and Risk-Free Rate, which are based on the selected country. The Equity Beta (β) is calculated as the 5-year Blume-adjusted beta between the weekly logarithmic returns of the underlying stock and the selected country’s stock market index. For accurate calculations, it is recommended to use the stock ticker listed on the primary exchange corresponding to the company’s main index.
Cost of Debt = (Interest Expense on Debt ÷ Average Debt) × (1 - Average Tax Rate)
Cost of Equity = Risk-Free Rate + Equity Beta (β) × (Index Return - Risk-Free Rate)
WACC = (MC ÷ (MC + Debt)) × Cost of Equity + (Debt ÷ (MC + Debt)) × Cost of Debt
This indicator works best for operationally stable and profitable companies that are primarily valued based on fundamentals rather than speculative growth, such as those in the industrial, consumer, technology, and healthcare sectors. It is less suitable for early-stage, unprofitable, or highly cyclical companies, including energy, real estate, and financial institutions, as these often have irregular cash flows or distorted balance sheets. It is also worth noting that TradingView’s financial data provider, FactSet, standardizes financial data from official company filings to align with a consistent accounting framework. While this improves comparability across companies, industries, and countries, it may also result in differences from officially reported figures.
In summary, the Intrinsic Value Analyzer is a comprehensive valuation tool designed to help long-term investors estimate a company’s fair value while comparing historical averages with the latest values. Fair value estimates are driven by growth forecasts, target multiples, and discount rates, and should always be interpreted within the context of the underlying assumptions. By default, the model applies historical averages and current discount rates, which may not accurately reflect future conditions. Investors are therefore encouraged to adjust inputs in the menu to better understand how changes in these key assumptions influence the company’s fair value.
Phân tích Cơ bản
Liquidity Sweep Filter [Magu]SMC The smart money concept in forex trading involves understanding the behavior of institutional players, such as banks and hedge funds, and analyzing supply and demand dynamics, order blocks, and price patterns.
SMC is often seen as a repackaged version of price action trading with a long history of producing positive results in various asset classes
Market liquidity is a fundamental concept in financial markets that significantly impacts trading strategies, asset pricing, and financial stability. The stock market is a prime example of a financial market where liquidity plays a crucial role in determining asset prices and trading strategies. Understanding market liquidity helps investors and traders make informed decisions, especially during times of market volatility. This article explores the key concepts, factors affecting liquidity, and strategies to navigate both liquid and illiquid markets
Smart Signal Pro™ | Multi-Timeframe Buy/Sell Alerts for Crypto━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚡ ZAKARIA SAFRI - SMART SIGNAL PRO™ v4.3
Advanced Multi-Timeframe Trading System 2025
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🎯 WHAT YOU GET:
✅ SMART BUY/SELL SIGNALS - AI-powered entry & exit alerts
✅ MULTI-TIMEFRAME DASHBOARD - 8 timeframes analyzed in real-time (3m to Daily)
✅ AUTO RISK MANAGEMENT - Stop Loss & 3 Take Profit levels calculated automatically
✅ TREND DETECTION - Color-coded ribbons, clouds & chaos trend lines
✅ REVERSAL ALERTS - Catch market reversals before they happen
✅ ORDER BLOCKS - Institutional supply/demand zones
✅ RSI OVERBOUGHT/OVERSOLD - Visual background alerts
✅ VOLATILITY METER - Know when markets are heating up
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💎 PERFECT FOR:
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📊 Day Traders - Scalp Bitcoin, Ethereum, altcoins
💰 Forex Traders - EUR/USD, GBP/USD, Gold, indices
📈 Stock Traders - SPY, AAPL, TSLA, any ticker
⏰ Swing Traders - Multi-day position trading
🔰 Beginners - Easy visual signals, no coding needed
⚡ Scalpers - Fast 3-minute signals
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🔥 KEY FEATURES:
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🎯 DUAL SIGNAL MODES:
• ALL SIGNALS - Maximum opportunities
• SMART SIGNALS - High-probability setups only
📊 LIVE MTF DASHBOARD:
• 3 Minute trend
• 5 Minute trend
• 15 Minute trend
• 1 Hour trend
• 2 Hour trend
• 4 Hour trend
• 12 Hour trend
• Daily trend
• Real-time RSI & Volatility readings
💰 AUTOMATED RISK TOOLS:
• Entry price marked
• Stop Loss calculated (ATR-based)
• Take Profit 1 (conservative)
• Take Profit 2 (moderate)
• Take Profit 3 (aggressive)
• TP alerts on chart
🎨 VISUAL TRADING AIDS:
• Candlestick coloring (3 modes)
• Trend ribbon (7 EMAs)
• EMA cloud (150/250)
• Chaos trend line
• Keltner channels
• Order blocks (optional)
• Channel breakouts
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⚙️ CUSTOMIZABLE SETTINGS:
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🔧 Adjust signal sensitivity (1-10)
🎨 Toggle any indicator on/off
📍 Dashboard position & size
🎯 Custom TP strength multiplier
🔔 Enable/disable specific features
📊 200 EMA adjustable
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🚀 WHY THIS INDICATOR?
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✔️ All-in-One Solution - No need for multiple indicators
✔️ Beginner Friendly - Clear buy/sell labels
✔️ Professional Grade - Institutional tools included
✔️ Works 24/7 - Crypto, Forex, Stocks, Futures
✔️ No Repainting - Signals stay fixed after close
✔️ Clean Interface - Not cluttered, easy to read
✔️ Regular Updates - Active development
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📈 TESTED ON:
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• Bitcoin (BTC/USD, BTC/USDT)
• Ethereum (ETH/USD, ETH/USDT)
• Altcoins (SOL, XRP, ADA, DOGE, SHIB)
• Forex Pairs (EUR/USD, GBP/USD, USD/JPY)
• Gold (XAU/USD)
• Indices (SPX, NASDAQ, DJI)
• Stocks (AAPL, TSLA, NVDA, AMZN)
• Futures & CFDs
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⏱️ BEST TIMEFRAMES:
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⚡ Scalping: 1min, 3min, 5min
📊 Day Trading: 15min, 30min, 1H
📈 Swing Trading: 4H, Daily
💼 Position Trading: Daily, Weekly
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🎓 HOW TO USE:
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1️⃣ Add indicator to any chart
2️⃣ Wait for BUY or SELL signal
3️⃣ Check dashboard for multi-timeframe confirmation
4️⃣ Enter trade at signal candle close
5️⃣ Set Stop Loss at marked level
6️⃣ Take profits at TP1, TP2, TP3 markers
7️⃣ Watch for reversal alerts to exit early
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⚠️ RISK DISCLAIMER:
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Trading involves risk. This indicator is a tool to assist your trading decisions, not financial advice. Always use proper risk management, never risk more than you can afford to lose, and backtest any strategy before live trading.
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📞 SUPPORT & UPDATES:
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💬 Questions? Comment below
⭐ Like this indicator? Leave a review!
🔔 Follow for updates and new releases
📊 Check my profile for more premium tools
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🏷️ TAGS:
buy sell signals, crypto trading, bitcoin indicator, forex signals, smart money, order blocks, multi timeframe analysis, day trading, scalping, swing trading, trend following, reversal trading, risk management, stop loss, take profit, trading dashboard, RSI indicator, ADX trend, professional trading
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© 2025 Zakaria Safri - Smart Signal Pro™
Version 4.3 | All Rights Reserved
Liquidity Channels - Zakaria Safri💎 LIQUIDITY CHANNELS PRO - BY ZAKARIA SAFRI
A professional-grade liquidity detection indicator that identifies and tracks buy-side and sell-side liquidity zones with expanding channels and real-time monitoring.
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🎯 WHAT IS LIQUIDITY?
Liquidity zones are areas where stop losses and pending orders cluster around swing highs and lows. Smart money often targets these zones before major moves. This indicator automatically detects and tracks these critical levels.
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✨ KEY FEATURES
🔵 Buy-Side Liquidity Detection
• Automatically identifies swing highs where stops cluster
• Tracks until price sweeps through the level
• Perfect for identifying potential reversals
🔴 Sell-Side Liquidity Detection
• Pinpoints swing lows with concentrated orders
• Monitors liquidity grabs in real-time
• Essential for SMC and ICT trading strategies
📊 Expanding Channels
• Visual representation of liquidity strength over time
• Wider channels = older, more significant liquidity
• Toggle on/off based on your preference
💎 Live Dashboard
• Real-time count of active liquidity levels
• Separate buy-side and sell-side tracking
• Movable to any corner of your chart
🎨 Full Customization
• Adjustable colors and line styles
• Pivot strength controls sensitivity
• Auto-cleanup of old untouched levels
• Channel transparency settings
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⚙️ HOW TO USE
1️⃣ ADD TO CHART
Apply the indicator to any timeframe
2️⃣ ADJUST PIVOT STRENGTH
• Higher values (30-50): Fewer, stronger zones
• Lower values (10-20): More sensitive detection
• Default (25): Balanced approach
3️⃣ WATCH FOR LIQUIDITY SWEEPS
• Price breaking above buy-side liquidity = Potential reversal down
• Price breaking below sell-side liquidity = Potential reversal up
• Look for reactions after sweeps
4️⃣ COMBINE WITH YOUR STRATEGY
• Works great with ICT concepts
• Perfect for Smart Money Concepts (SMC)
• Complements order block strategies
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🎓 BEST PRACTICES
✅ Use on higher timeframes (H1, H4, Daily) for stronger zones
✅ Look for multiple liquidity levels clustered together
✅ Watch for sweeps during high-volume sessions
✅ Combine with support/resistance for confirmation
✅ Wait for price reaction after liquidity grab
❌ Don't use as sole trading signal
❌ Avoid over-optimization of parameters
❌ Don't ignore overall market context
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📈 IDEAL FOR
• Smart Money Concept (SMC) traders
• ICT methodology followers
• Swing traders
• Liquidity sweep strategies
• Order flow analysis
• Stop hunt identification
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⚡ SETTINGS OVERVIEW
🎨 Visual Settings
• Customizable colors for buy/sell liquidity
• 3 line styles: Solid, Dashed, Dotted
• Adjustable line thickness (1-5)
• Channel transparency control
⚙️ Detection Settings
• Pivot Strength: Sensitivity control
• Channel Expansion: Growth rate adjustment
🧹 Management Settings
• Auto-delete old untouched levels
• Adjustable bar count for cleanup
📊 Dashboard
• Toggle info panel on/off
• 4 position options
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💡 PRO TIPS
🎯 Liquidity Sweep Entry
When price sweeps liquidity and reverses, look for entry on lower timeframe confirmation
🎯 Multiple Timeframe Analysis
Mark liquidity zones from higher timeframes on your execution timeframe
🎯 Session Trading
London and New York opens often target liquidity before trending
🎯 Confluence Zones
Areas where buy-side and sell-side liquidity converge are high-probability zones
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📞 SUPPORT & UPDATES
This indicator is actively maintained and updated.
Feedback and suggestions are welcome!
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⚠️ DISCLAIMER
This indicator is for educational purposes only. No trading tool guarantees profits. Always use proper risk management and combine with your own analysis. Past performance does not indicate future results.
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© 2024 Zakaria Safri - All Rights Reserved
💎 Trade Smart. Trade with Liquidity Awareness.
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🏷️ Tags: Liquidity, Smart Money Concepts, SMC, ICT, Order Flow, Stop Hunt, Liquidity Sweep, Order Blocks, Market Structure, Institutional Trading
Fear–Greed Index
What it does
This indicator compresses multiple behavioral signals into a single Fear–Greed Index (FGI) that ranges from –100 (extreme fear) to +100 (extreme greed). It blends three psychology-based components—Prospect Theory, Herding, and Social Impact Theory (SIT)
How it thinks
Prospect Theory (CPT)
Looks at the balance of gains vs. losses in recent returns.
Herding (Brock–Durlauf / Ising-style)
Counts the signs of recent returns (up vs. down) to measure “magnetization” (are most bars up or down.
Social Impact Theory (SIT)
Measures today’s return strength relative to recent volatility (strength), how concentrated recent moves were in the most recent quarter of the window (immediacy), and participation via volume relative to its recent average (number).
How to use it
Rising toward +100 → crowd risk-on/greed; falling toward –100 → risk-off/fear.
Treat extreme zones as context, not standalone trade signals—combine with price structure, volume, and risk management.
Quarterly Financials on Chart with Estimates by SpeedEdge)# Quarterly Financials on Chart with Estimates
## WHAT THIS SCRIPT DOES
This indicator displays comprehensive quarterly financial data directly on your trading chart, eliminating the need to switch between charting and fundamental analysis platforms. The script automatically fetches and organizes key financial metrics including earnings per share (EPS), revenue, operating margins, depreciation & amortization, and quarterly estimates alongside actual results for comparative analysis.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Traders conducting fundamental analysis typically need to toggle between trading charts and separate financial platforms to view quarterly results, estimates, and year-over-year comparisons. This workflow is inefficient and makes it difficult to correlate price movements with earnings announcements.
**The Solution:** This script integrates fundamental financial data directly into the price chart environment, providing:
- Side-by-side comparison of quarterly estimates versus actual results
- Automatic calculation of Quarter-over-Quarter (QoQ) and Year-over-Year (YoY) growth rates
- Color-coded visualization of financial performance trends
- Regional number formatting (Indian Crores or Global Billions/Millions)
- Key valuation metrics (Market Cap, Free Float, PEG Ratio, CFO/EBITDA) in header
**Unique Features:**
1. **Dual Number Format System**: Automatically formats financial figures in Indian Crores (Cr, K Cr, L Cr) or Global formats (M, B, T) based on user preference
2. **Estimate Integration**: Shows analyst estimates for upcoming quarters alongside historical actuals for beat/miss analysis
3. **Intelligent Growth Analysis**: Automatically calculates and color-codes quarterly and yearly growth comparisons with smart handling of missing data
4. **Context-Aware Color Coding**: Green/red visualization adapts based on metric type - growth metrics, cash flow quality indicators, and expense trends each use appropriate color logic
5. **Configurable History**: Display 4 to 20 previous quarters based on analysis needs
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Methodology:
**1. Financial Data Integration:**
The script accesses quarterly and annual financial statement data from public company filings, including:
- **Earnings Estimates**: Analyst consensus forecasts for upcoming quarters
- **Quarterly Actuals**: Reported earnings per share, revenue, margins, and operating expenses
- **Key Ratios**: Shares outstanding data, valuation multiples, and cash flow metrics
All data is sourced from TradingView's fundamental database, which aggregates information from official regulatory filings (10-Q, 10-K, annual reports) filed by publicly traded companies.
**2. Historical Data Organization:**
The script employs a sophisticated data structure system that:
- Detects when new quarterly results are released by monitoring data changes
- Automatically indexes financial data by quarters relative to the current date
- Creates a chronological timeline of financial performance
- Maintains historical records for comparison calculations
- Updates dynamically as new earnings are reported
**3. Intelligent Number Formatting:**
**Indian Regional Format:**
- Converts absolute values to Crore denomination (1 Crore = 10 Million)
- Scales to Thousand Crores (K Cr) for mid-size companies
- Scales to Lakh Crores (L Cr) for large corporations
- Appropriate for analyzing Indian market stocks
**Global Standard Format:**
- Uses Million (M) for smaller companies
- Scales to Billion (B) for mid-cap and large-cap stocks
- Uses Trillion (T) for mega-cap corporations
- Thousands (K) for smaller financial figures
- Standard across US and international markets
**4. Comparative Growth Analysis:**
**Quarter-over-Quarter (QoQ) Calculations:**
The script compares each quarter's performance against the immediately preceding quarter to identify:
- Sequential growth trends
- Momentum acceleration or deceleration
- Short-term business trajectory
- Seasonal pattern changes
**Year-over-Year (YoY) Calculations:**
Compares each quarter against the same quarter from the previous year to:
- Eliminate seasonal effects
- Identify sustainable growth trends
- Normalize for business cycles
- Provide apples-to-apples comparison
Both calculations automatically handle edge cases like missing data, account for different fiscal year conventions, and provide meaningful "N/A" indicators when comparative data is unavailable.
**5. Adaptive Color Coding System:**
**Growth Metrics (EPS, Revenue):**
- Positive growth → Green shading indicates improving performance
- Negative growth → Red shading signals declining performance
- Missing data → Gray indicates insufficient information
**Quality Indicators (Free Float %):**
- Lower float (<40%) → Green indicates potentially better supply-demand dynamics
- Higher float (≥40%) → Red suggests more diluted ownership
**Cash Flow Quality (CFO/EBITDA):**
- Strong cash conversion (≥50%) → Green shows quality earnings
- Weak cash conversion (<50%) → Red flags potential accounting concerns
**Expense Trends (Depreciation & Amortization):**
- Decreasing D&A → Green indicates improving cash flow characteristics
- Increasing D&A → Red suggests rising capital intensity
- Stable D&A → Default color shows consistency
**Future Estimates:**
- Yellow coloring clearly distinguishes forward-looking estimates from historical actuals
**6. Date and Quarter Intelligence:**
The script automatically:
- Determines the current financial quarter based on real-time date
- Maps calendar months to fiscal quarters (Q1-Q4)
- Handles different fiscal year conventions globally
- Calculates quarter differentials for accurate historical lookback
- Formats display labels showing quarter-end months and years (e.g., "Mar 24", "Dec 23")
### Advanced Calculations:
**Free Float Percentage:**
Calculates the proportion of shares available for public trading relative to total shares outstanding. Lower percentages indicate more concentrated ownership, which can affect volatility and liquidity.
**Market Capitalization:**
Real-time calculation using total shares outstanding multiplied by current market price, automatically updated with each price tick and formatted according to regional preferences.
**CFO/EBITDA Cash Quality Ratio:**
Measures what percentage of accounting earnings converts to actual operating cash flow. Higher ratios indicate better earnings quality and less aggressive accounting. Industry standards vary, but 60-100% typically signals strong cash generation.
**Operating Profit Margin Tracking:**
Monitors the percentage of revenue retained as operating profit after deducting operating expenses, providing insight into operational efficiency and pricing power trends.
## HOW TO USE THIS SCRIPT
### Initial Setup:
**1. Region Configuration:**
- **India**: Select for Indian stocks - formats numbers in Crores (₹10M = 1 Cr)
- **Global**: Select for international stocks - formats in Millions/Billions
**2. Display Settings:**
- **Position**: Choose table location on chart (Top Right recommended)
- **Table Size**: Adjust based on screen resolution (Normal is default)
- **Short Labels**: Enable to condense industry/sector names for space saving
- **Lookback Quarters**: Set how many previous quarters to display (4-20, default 5)
**3. Visual Customization:**
- **Background Color**: Customize table background color and transparency
- **Text Color**: Adjust text color for visibility
- **Border/Frame Colors**: Modify table borders for preferred appearance
### Reading the Dashboard:
**Header Section (Top 3 Rows):**
**Row 1:**
- **Ticker | Mcap**: Company symbol and current market capitalization
- **FF (Free Float)**: Percentage of freely traded shares (Green < 40% is positive, Red ≥ 40%)
- **CFO/EBITDA**: Cash flow quality ratio (Green ≥ 50% is positive, Red < 50%)
**Row 2:**
- **Industry**: Company's specific industry classification
- **Sector**: Broader sector classification
- **PEG Ratio**: Price/Earnings to Growth ratio (< 1 traditionally considered undervalued)
**Data Section:**
**Column Explanations:**
1. **Fin Q**: Financial quarter (format: "Mar 24" = Q4 FY2024 ending March)
2. **EPS**: Earnings Per Share in reporting currency
3. **QoQ %**: EPS growth versus previous quarter (Green = increase, Red = decrease)
4. **YoY %**: EPS growth versus same quarter last year
5. **Sales**: Total revenue (formatted in Cr or M/B based on region)
6. **QoQ %**: Revenue growth versus previous quarter
7. **YoY %**: Revenue growth versus same quarter last year
8. **OPM %**: Operating Profit Margin percentage
9. **D&A**: Depreciation & Amortization (Green if decreasing = cash flow positive)
**Estimates Row (Yellow Text):**
- Shows "Q Est." for upcoming quarter
- Displays analyst consensus estimates for EPS and Sales
- Compare actuals against estimates after earnings release to identify beats/misses
### Trading Applications:
**Fundamental Analysis:**
- **Earnings Quality Check**: Look for consistent QoQ and YoY growth in both EPS and Sales
- **Margin Trend Analysis**: Monitor OPM % changes to assess operational efficiency
- **Estimate Comparison**: Identify stocks that consistently beat or miss estimates
- **Cash Flow Validation**: Use CFO/EBITDA ratio to verify earnings quality
**Entry/Exit Timing:**
- **Post-Earnings Analysis**: Check if stock beat estimates and by what margin
- **Trend Confirmation**: Strong YoY growth + improving margins = positive fundamentals
- **Warning Signs**: Declining margins, negative growth, or deteriorating CFO/EBITDA
**Portfolio Screening:**
- **Growth Stocks**: Look for consistent QoQ and YoY EPS/Sales growth
- **Value Stocks**: Low PEG ratios combined with positive fundamentals
- **Quality Filter**: High CFO/EBITDA ratios (>75%) indicate superior cash generation
### Interpretation Guidelines:
**Strong Fundamental Setup:**
- YoY growth > 15% in both EPS and Sales
- QoQ growth positive for 2+ consecutive quarters
- OPM % stable or improving
- CFO/EBITDA > 60%
- Actual results exceed estimates
**Concerning Signals:**
- Declining YoY growth rates
- Shrinking operating margins
- Consistently missing estimates
- CFO/EBITDA < 40%
- Increasing D&A as percentage of revenue
## IMPORTANT USAGE NOTES
**Data Limitations:**
- Financial data depends on official company filings and reporting schedules
- Some stocks may have incomplete historical data depending on listing history
- Estimates may not be available for all companies, especially smaller-cap stocks
- Data updates occur after official earnings releases, not in real-time during announcements
**Realistic Expectations:**
- This tool displays historical fundamental data for analysis - not predictive signals
- Always verify critical financial data with official company filings when making investment decisions
- Fundamental analysis should complement technical analysis, not replace it
- Past financial performance does not guarantee future results
- Earnings estimates are analyst opinions, not certainties
**Best Practices:**
- Cross-reference important data points with company investor relations pages
- Consider industry-specific metrics beyond the displayed general figures
- Use in conjunction with technical indicators for comprehensive analysis
- Monitor for data anomalies (stock splits, accounting changes, restatements) that may affect comparisons
- Understand that different accounting standards (GAAP vs IFRS) may affect international comparisons
**Regional Considerations:**
- Indian stocks: Numbers in Crores (1 Cr = 10 Million Rupees)
- Global stocks: Numbers in standard M/B/T format
- Currency conversions are not performed - data shown in reporting currency
- Fiscal year conventions vary by region (India typically uses Apr-Mar fiscal year, US uses Jan-Dec or custom fiscal years)
- Different markets have different reporting timelines and requirements
## CONFIGURATION RECOMMENDATIONS
**For Indian Stocks:**
- Region: India
- Lookback: 5-8 quarters (recommended)
- Focus on YoY growth due to seasonal business patterns in many Indian companies
**For US/Global Stocks:**
- Region: Global
- Lookback: 4-6 quarters for tech/growth stocks
- Lookback: 8-12 quarters for cyclical/industrial stocks
- Monitor QoQ trends closely for rapid-growth sectors
**For Long-term Investors:**
- Increase lookback to 12-20 quarters to see multi-year trends
- Focus on consistency rather than individual quarter volatility
- Pay close attention to CFO/EBITDA quality metric for sustainable businesses
- Look for stable or improving margins over extended periods
**For Active Traders:**
- Use 4-6 quarter lookback for recent trend focus
- Concentrate on latest QoQ trends and estimate beats/misses
- Monitor table closely before/after earnings announcements
- Compare estimate versus actual immediately post-earnings for trading opportunities
**For Swing Traders:**
- 6-8 quarter lookback provides good balance
- Focus on acceleration/deceleration in growth rates
- Use margin trends to identify operational inflection points
- Combine with technical analysis for optimal entry/exit timing
This script serves as a comprehensive fundamental analysis tool for traders and investors who want seamless chart integration of financial data without workflow interruption, enabling faster and more informed decision-making.
MariTrades Gold Indicator B-Stop loss and Take profitsThe MariTrades Gold Indicator B is an original Trading View script designed to help traders visualize entry points, stop loss (SL), take profit (TP), and key structure levels on gold charts. This publication fully complies with Trading View’s public script rules, including originality, English description, chart clarity, and Pine Script v5 usage.
Key Features:
Break of Structure (BOS) Detection:
Detects trend reversals by identifying when price closes above/below the previous swing high/low.
BOS signals are marked on the chart for both buy and sell opportunities.
Fibonacci Retracement Levels:
Automatically plots retracements from the last swing high to swing low.
(NOT LABELLED)
Entry signals are confirmed when price retraces to these levels after BOS.
Automatic SL and TP Visualization:
Stop loss and take profit levels are drawn directly on the chart.
Default values: SL = 5 pips, TP = 10 pips (customizable via inputs).
Entry Signals:
Buy: Price breaks structure (BOS) and retraces to Fibonacci level → label and lines drawn.
Sell: Price breaks structure (BOS) and retraces to Fibonacci level → label and lines drawn.
Clean, readable chart overlay:
Previous signals are automatically removed to avoid clutter.
SL lines in red, TP lines in green, entry labels clearly displayed.
Integral Signal (Volume & Price Analysis) v6 - Final# 📈 Integral Signal v6: Volume and Price Momentum Aggregator
**The Integral Signal v6** is a comprehensive, multi-factor indicator designed to cut through market noise by aggregating five crucial volume and price momentum factors into a single, reliable score. This tool is ideal for traders looking for high-conviction entry and exit points, validated by both immediate pressure (CVD) and long-term structure (VRVP).
The indicator generates a score ranging from **-1.0 to +1.0**, where a higher absolute value indicates greater consensus among factors, leading to a high-probability signal.
### 📊 How the Score is Calculated (The Five Factors)
The Integral Score is a weighted average of the following market forces:
1. **CVD Imitation (Cumulative Volume Delta):** Measures the rate-of-change (ROC) for both price and volume to gauge immediate buying/selling pressure.
2. **Open Interest (OI) Imitation:** Assesses whether price movement is supported by significant volume spikes (a proxy for genuine participation).
3. **Liquidations Imitation:** Identifies major volatility spikes combined with new lows/highs, signaling potential 'squeezes' and reversals.
4. **Funding Rate Imitation:** Uses RSI overbought/oversold levels to proxy market overheating and sentiment.
5. **VRVP Imitation (Volume Profile Structure):** Utilizes a 50-period Simple Moving Average (SMA) to filter signals based on the overall trend and structural support/resistance.
### ✨ Key Features
* **High-Conviction Signals:** Signals are triggered only when the Integral Score crosses a user-defined threshold (e.g., 0.85), requiring multiple factors to align.
* **Dual Filtering:** Includes optional MACD and RSI filters to ensure signals only fire when the underlying trend momentum is supportive.
* **Adaptability:** Separate optimal settings are provided for aggressive short-term trading (Scalping) and high-reliability long-term positioning (Swing Trading).
---1. Scaling / Aggressive Trading (15m Timeframe)
Use these settings for short-term entry/exit points and day trading. They are designed to capture quick momentum shifts with reduced but still present noise.
Parameter Category Parameter Name Value Notes
Threshold Signal Threshold (-1 to +1) 0.8 Requires high momentum consensus.
Weight Weight: CVD 0.40 High priority for immediate pressure.
Weight Weight: Open Interest 0.15 Reduced priority.
Weight Weight: Liquidations 0.10 Reduced priority due to noise.
Weight Weight: Funding Rate 0.05 Minimal priority on 15m.
Weight Weight: VRVP (SMA Zone) 0.30 High priority for trend filtering.
Filter Use RSI Filter True
Filter RSI Period 14 Standard, responsive setting.
Filter Use MACD Filter True
Экспортировать в Таблицы
2. Swing Trading / High Reliability (4H / 1D Timeframe)
Use these settings for signals intended to hold positions for days or weeks. They are heavily weighted towards long-term structural confirmation.
Parameter Category Parameter Name Value Notes
Threshold Signal Threshold (-1 to +1) 0.85 Highly restrictive, requires strong consensus.
Weight Weight: CVD 0.45 Highest priority for major buying/selling pressure.
Weight Weight: Open Interest 0.10 Low priority.
Weight Weight: Liquidations 0.05 Lowest priority (to filter short-term volatility).
Weight Weight: Funding Rate 0.10 Increased weight, useful for identifying market "overheating" on higher TFs.
Weight Weight: VRVP (SMA Zone) 0.30 High priority for trend confirmation.
Filter Use RSI Filter True
Filter RSI Period 21 Smoother, more reliable RSI for longer timeframes.
Filter Use MACD Filter True
Экспортировать в Таблицы
EPS↑ & PER(CN)↓ DetectorEPS↑ × PER(CN)↓ Detector — Fundamental Signal & Screener Friendly
This indicator detects periods where EPS increases while Cash-Neutral PER (PER(CN)) decreases simultaneously —
a classic fundamental early-stage signal for growth stocks at attractive valuations.
It tracks EPS and PER(CN) per earnings period and is fully compatible with TradingView Screener.
📝 Key Features
✅ EPS↑ × PER(CN)↓ Signal on period change (earnings update)
✅ Displays EPS Growth %, PER(CN), PEG(CN), NCR%, Market Cap, Float Ratio in a compact table
✅ Size-aware PER(CN) thresholds and PEG(CN) lanes to screen large caps effectively
✅ Screener outputs (Screen OK, PEG, PER cap, periods since signal, etc.) for systematic filtering
📈 Use Cases
Identify early-stage growth stocks based on fundamental shifts
Build earnings-driven screeners using EPS↑×PER↓ logic
Spot undervalued growth phases in both small and large caps using PEG and size-aware filters
⚠️ Notes
Missing EPS data defaults to a fallback PER value.
Financial data availability may lag depending on reporting schedules.
PEG(CN) calculations apply a floor to low growth rates.
📌 A powerful tool to automatically detect and visualize “growth + value” inflection points, ideal for earnings-based screening and medium–long term investing strategies.
================
🇯🇵 EPS↑ × PER(CN)↓ Detector — ファンダメンタル初動シグナル & スクリーナー対応
このインジケーターは、EPS（1株利益）の上昇と、Cash Neutral PER（PER(CN)）の低下が同時に発生したタイミングを検出し、
成長株の初動や割安成長局面をファンダメンタル面から捉えるためのツールです。
EPSとPER(CN)の変化を決算期ごとに追跡し、スクリーナーでも利用できるよう軽量化されています。
💡作成した経緯
清原 達郎さんが勧めているEPS成長率が上がっている銘柄でPERが追いついていない企業をいち早く察知したいと思ったのがきっかけ。
ファンダがわからない人でも数値の色が赤くなっていれば、とりあえず成長が加速しているんだと判断できるのをゴールに作成しました。
企業の稼ぐ力が上がっているのに、株価が割安になったタイミングでサインが出るため、適正価格までの上昇値幅が期待できます。
📝 主な機能
✅ EPS↑ × PER(CN)↓ シグナル検出
決算更新時に EPS が前期比で上昇 & PER(CN) が低下した場合にシグナルを点灯
✅ EPS成長率・PER(CN)・PEG(CN) など、成長性・割安性を多角的に数値化
✅ 時価総額に応じたPER上限判定（サイズ連動） や PEG(CN)レーン に対応し、
大型銘柄も拾えるスクリーニング条件を組み込み
✅ **テーブル表示（右上）**で各指標をリアルタイム確認（EPS, PER(CN), PEG, NCR%, EPS成長率, 時価総額, 浮動株比率）
✅ スクリーナー列を出力（Screen OK, PEG(CN), PER上限、シグナル経過期間 など）
📈 活用イメージ
上記画像のように、三角マークが描画された数日後から上昇トレンドが開始しているのが見て取れます。
三角マークが描画されなくても、EPS成長率が100を超える場合やPEGが1以下の場合など割安である可能性がある数値の場合は赤文字になる仕様です。
注意点として、高EPS成長率、PEG1以下、低PERでもNCRがマイナスの場合は
負債によって引き起こされる見かけ騙しのEPS成長率の時があります。
その際はNCRが緑文字になります。
銀行・証券・保険などの金融セクターや、一部の持株会社／投資会社では指標の意味が歪みやすいため緑になっても問題ありません。
⚠️ 注意点
EPS または PER データが欠損している場合、デフォルトPERを使用します。
財務データは更新のタイミングによって表示が遅れることがあります。
PEG(CN)の計算では、EPS成長率が小さい場合にフロア値を適用しています。
🚀🚀 PROFABIGHI_CAPITAL Correlation Heatmap System 🚀🚀🌟 Overview
The PROFABIGHI_CAPITAL Correlation Heatmap System is an institutional-grade multi-asset correlation visualization tool engineered for cryptocurrency traders seeking to dissect inter-asset dependencies and portfolio risk clustering through dynamic, rolling correlation matrices or benchmark-focused comparisons. By computing Pearson correlation coefficients over adjustable lookback periods across up to 20 symbols, it generates color-coded heatmaps highlighting positive (green) or negative (red) relationships, while the single-asset mode benchmarks against a primary symbol (e.g., BTC) to reveal relative strength hierarchies , top/bottom extremes, and diversification insights—empowering users to optimize allocations, detect co-movement risks , or uncover decoupling opportunities in volatile markets with real-time table updates and symmetric visualizations.
This sophisticated system transcends basic scatter plots by offering dual-mode flexibility —comprehensive pairwise matrices for broad ecosystem scanning or targeted single-asset scans for focused relative analysis—complete with invalid symbol tolerance , dynamic table sizing , and performance-optimized fetching , ensuring seamless scalability from watchlists of 5 assets to full 20-symbol universes while maintaining computational efficiency and visual clarity for professional-grade decision-making.
🚀 Main Settings
- Display Mode : Core selector between 'X -> Y Matrix' for exhaustive pairwise correlation grids that reveal the full network of asset interdependencies, ideal for identifying clusters of high-beta alts or low-correlation hedges, and 'Single Asset R Comparison' for streamlined benchmarking against a chosen primary symbol, perfect for evaluating how individual tokens align or diverge from market leaders like BTC during regime shifts
- Correlation Length : Adjustable rolling window (default 30 bars) that defines the historical scope for coefficient calculations, where shorter periods emphasize recent volatility correlations for tactical adjustments and longer horizons capture structural relationships for strategic portfolio construction, balancing noise reduction with regime sensitivity
- Number of Assets in Matrix : Scalable limit (up to 20) controlling the heatmap dimensions, enabling focused 5x5 grids for core holdings or expansive 20x20 matrices for ecosystem-wide scanning, with automatic diagonal suppression (em-dashes) to avoid self-correlation artifacts and optimize visual density
📊 Single Asset R Comparison Settings
- The PROFABIGHI_CAPITAL Asset : Primary symbol designation (default BTCUSD) serving as the correlation anchor, allowing traders to assess how alts co-move with this reference during pumps, dumps, or sideways action, facilitating relative strength rankings and beta-like exposure profiling without full regressions
- Number of Assets in Main Table : Configurable count (up to 20) for the unsorted correlation list, providing a comprehensive yet manageable view of dependencies in original input order, useful for sequential portfolio reviews or quick scans of predefined watchlists
- Number of Top/Bottom Assets : Highlight limit (default 5) for dedicated tables showcasing strongest positive (top) and weakest/negative (bottom) correlations, spotlighting diversification candidates (low R) or momentum followers (high R) to guide rebalancing decisions amid market rotations
📈 Assets List (20x)
- Asset 1 through Asset 20 : Sequential symbol inputs for building the correlation universe, starting with majors like BTC, ETH, SOL for baseline stability and extending to alts like XRP, ADA for diversification insights, with tooltip guidance for format (e.g., CRYPTO:BTCUSD) and flexibility for custom tokens across exchanges
- Grouped Configuration : Organized list for streamlined portfolio assembly, allowing quick swaps of underperformers or additions of emerging narratives, ensuring the heatmap reflects current market themes from blue-chips to speculative plays
- Exchange Prefix Support : Native handling of prefixed symbols (e.g., CRYPTO:, BINANCE:), enabling cross-platform comparisons without manual adjustments, while the short name extractor cleans displays for readability in dense tables
📡 Data Fetching (20x)
- Parallel Security Requests : Simultaneous close price pulls for all 20 assets using timeframe-aligned fetches, ensuring synchronized data across symbols to maintain correlation accuracy even in asynchronous market hours
- System Asset Isolation : Dedicated retrieval for the primary benchmark symbol, preventing contamination in single-mode comparisons and allowing independent updates without affecting matrix computations
- Invalid Symbol Resilience : Built-in ignore_invalid_symbol parameter with na defaults, gracefully handling malformed inputs or delisted tokens to avoid script crashes and enable partial universe analysis
- Chart Timeframe Alignment : Automatic adaptation to the active chart resolution, supporting from 1-minute intraday correlations for scalping to daily for swing trading, with consistent bar indexing for reliable rolling windows
🔧 Helper Functions
- Short Name Extractor : Utility to strip exchange prefixes and suffixes (e.g., CRYPTO:BTCUSD → BTC), generating compact labels for table headers and cells, enhancing scannability in large matrices without losing symbol identity
- Correlation Column Generator : Core function computing Pearson coefficients between two series over the specified length, returning both the value and a binary color (green for positive >0, red for negative) to streamline heatmap cell population with visual intuition
- Cell Filler Routine : Standardized table.cell wrapper applying consistent black-transparent backgrounds, small text sizing, and dynamic text colors, ensuring uniform aesthetics across all visualization modes while supporting conditional formatting for emphasis
📊 Correlation Calculations
- Pairwise Rolling Coefficients : Exhaustive computation of ta.correlation for every unique asset pair (up to 190 in 20x20 mode), generating symmetric matrices that illuminate co-movement patterns, from tight BTC-ETH linkages to decoupled niche alts, with na-safe handling for data gaps
- Single-Asset Benchmark Series : Dedicated correlations against the primary symbol for all others, producing a vector of R values that quantify relative dependencies, enabling quick identification of 'BTC clones' (high positive) or inverse hedges (negative)
- Length-Parameterized Rolling : Each coefficient uses the user-defined lookback to filter transient noise, where 20-bar windows highlight short-term spillovers and 100-bar captures enduring regime correlations for long-term allocation
- Color Mapping Logic : Binary green/red assignment based on sign (positive/negative), providing immediate visual cues for diversification (seek reds) or momentum trading (cluster greens), with potential for gradient extensions in future iterations
- Diagonal Suppression : Automatic em-dash placement on self-correlations (always 1.0), avoiding redundant cells and centering focus on inter-asset insights in the heatmap grid
🎨 Visualization Logic
- Last-Bar Dynamic Refresh : Table recreation on barstate.islast with prior deletions to prevent accumulation, ensuring crisp updates without historical artifacts or memory bloat in extended sessions
- Branding Banner Table : Bottom-center single-cell overlay with bold, yellow-texted indicator title on black background, serving as persistent identifier and visual anchor amid multi-table layouts
- Matrix Heatmap Construction : Centered (num_assets+1)x(num_assets+1) table with gray borders, populating headers vertically/horizontally with short names, filling off-diagonals with formatted R values and sign-based colors for symmetric, at-a-glance dependency mapping
- Single-Mode Multi-Table Suite : Top-center primary asset highlight (yellow-bordered), middle-center unsorted main list for sequential review, left/right top/bottom sorted subsets for extreme correlation spotlights, all with gray headers and color-coded R cells
- Progressive Cell Population : Nested conditionals scaling fills to active asset count, ensuring partial matrices render cleanly while full 20x20 grids showcase exhaustive pairwise analysis without overflow
- Error Handling Label : Fallback red downward label when no valid correlations available, prompting data checks and preventing blank displays in edge cases like all-invalid symbols
✅ Key Takeaways
- Dual-Mode Versatility : Seamlessly toggles between exhaustive pairwise heatmaps for ecosystem mapping and single-asset benchmarks for relative strength profiling, adapting to tactical or strategic analysis needs
- Rolling Correlation Insights : Adjustable windows reveal dynamic dependencies, crucial for spotting co-crash risks (high positive R) or counter-trend hedges (negative R) in crypto's correlated environments
- Visual Heatmap Efficiency : Color gradients and symmetric layouts enable instant pattern recognition, from BTC-beta clusters to low-R diversification gems, accelerating portfolio optimization
- Scalable Asset Handling : Up to 20 symbols with invalid tolerance and dynamic sizing, supporting watchlist scans without performance hits or manual exclusions
- Top/Bottom Extremes : Dedicated tables flag strongest/weakest links, guiding quick rebalances toward uncorrelated assets for reduced drawdowns or amplified momentum plays
- Benchmark-Centric Flexibility : Custom primary symbol centers analysis on user priorities like ETH for DeFi focus, transforming raw R values into actionable relative performance hierarchies
智能资金概念-NEWSmart Fund Concept-NEW
Smart Fund Concept-NEW
Smart Fund Concept-NEW
Smart Fund Concept-NEW
Smart Fund Concept-NEW
Volume Profile Two-Tone - Hit Counter - Meter V1 Volume Profile Two-Tone - Hit Counter - Meter V1
Overview
The Volume Profile Two-Tone - Hit Counter - Meter V1 is a Pine Script v6 indicator for TradingView, designed to visualize buy and sell activity distribution across price levels within a user-defined window or intraday session. It plots a dual-color horizontal histogram showing buying (green) and selling (red) volume intensity, along with optional hit-count numbers and meter overlays. The profile dynamically updates as new bars form, providing an intuitive picture of where market participants are most active.
The enhanced V1 edition introduces persistent hit counts, real-time adaptive row rebuilding, and improved memory management for smoother performance in both rolling-window and session modes.
How It Works
The indicator divides the selected range into rows (price bins) and aggregates trade volume (or tick volume) per bar.
Each bin separately sums up bullish and bearish contributions based on candle direction and delta logic, then draws side-by-side histogram bars:
• Buy Volume (green): Total volume from bullish bars within the bin.
• Sell Volume (red): Total volume from bearish bars within the bin.
A rolling or session-based window determines how many recent bars are analyzed. Value Area (VA), Point of Control (POC), and total hits per bin are computed continuously. The display auto-adjusts as price moves, keeping the profile anchored to the latest visible bars.
Behind the scenes, optimized arrays manage active boxes, lines, and labels for each bin. Functions like ensure_rows() rebuild buffers only when necessary, guaranteeing efficiency without repainting past data. Persistent hit-tracking ensures each price level maintains its count even when temporarily hidden.
Key Features
• Dual-Tone Volume Histogram: Buy/sell split with distinct colors for immediate visual contrast.
• Rolling or Session Profiles: Choose between continuous rolling windows or intraday session resets.
• Persistent Hit Counts: Displays total touches per bin, remaining stored even when bins refresh.
• Adaptive Row Management: Automatic rebuilding when zooming, scrolling, or changing resolution.
• Value Area + POC Detection: Highlights the most active price levels and volume concentration zones.
• Meter Overlay Option: Adds gradient bars or directional meters for quick trend context.
• Performance Optimized: Uses lightweight arrays and cached line handles for minimal CPU load.
• Custom Color Control: Editable buy/sell colors, opacity, row count, and profile width.
• Full Persistence Mode: Profiles remain visually consistent across bar updates without redraw gaps.
What It Displays
The Volume Profile Two-Tone - Hit Counter - Meter V1 presents an adaptive horizontal histogram beside the chart’s candles, revealing how volume is distributed across price.
• Green segments show dominant buying interest; red segments reveal selling pressure.
• POC line identifies the highest-volume price.
• Hit-count numbers quantify how often price traded at each level.
• Optional meters display relative directional strength within the same range.
This visual layering helps traders quickly identify supply/demand zones, balance areas, and developing auction profiles across intraday or multi-session contexts.
Originality
The Pine Script v6 indicator uses efficient array management (array.new_*, array.set, array.get) and native math operations for rendering.
It avoids external dependencies, relying only on built-in TradingView functions like request.security, box.new, line.new, and label.new for dynamic plotting.
Common Ways People Use It
• Scalpers: Study short-term imbalances or high-activity levels to time entries/exits.
• Day Traders: Track evolving session volume and POC migration.
• Swing Analysts: Compare rolling distributions to identify value shifts over multiple days.
• Volume Profilers: Combine with VWAP or order-flow tools for deeper context.
Configuration Notes
Profile Mode: Select Rolling Window (bars) or Session (intraday).
Rows and Width: Default = 72 rows, 44 bars width.
Colors and Opacity: Adjust to match chart theme.
Performance Mode: Choose Accurate or Fast (approximate) for speed control.
Show Hits / Meter: Enable hit-count numbers and gradient meters for added context.
Legal Disclaimer
For informational and educational purposes only—not investment, financial, or trading advice. Past performance does not guarantee future results; trading involves significant risk. Provided “as is,” without warranties. Consult a qualified professional before making decisions. By using, you accept all risks and agree to this disclaimer.
Advanced Memecoin Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Advanced Memecoin Tracker -> PROFABIGHI_CAPITAL is a specialized multi-chain memecoin intelligence dashboard that integrates relative strength positioning (RSP) via RSI on asset ratios with benchmark-relative metrics to score up to 36 memecoins across Ethereum, Solana, SUI, and BASE/VIRTUAL ecosystems. It computes weighted composites from outperformance binaries, category-leading RSP flags, and rank-based points, visualized in expansive tables for median benchmarking and top rankings to pinpoint viral momentum leaders amid speculative volatility.
🔧 General Settings
- Toggle for activating alpha to isolate excess returns beyond benchmark influence, highlighting unique memecoin drivers
- Toggle for enabling beta to quantify volatility correlation with the benchmark, aiding memecoin risk profiling
- Toggle for incorporating Sharpe ratio to gauge overall efficiency of returns relative to total risk exposure
- Toggle for including Sortino ratio to prioritize returns adjusted specifically for downside volatility impacts
- Toggle for utilizing omega ratio to weigh probability-adjusted gains against losses above a target threshold
- Toggle for adding rate of change (ROC) to capture raw momentum shifts over a specified horizon
- Adjustable lookback periods for alpha and beta regressions, tuning between stability and recency in relative analysis
- Customizable benchmark symbol , such as market indices, to establish the reference frame for comparative evaluations
- Configurable Sharpe rolling window and smoothing for responsive risk-reward snapshots
- Extended Sortino and omega periods with risk-free rates and target returns for robust downside and distributional insights
- ROC horizon setting to balance short-term reactivity with trend confirmation
- Scalable asset count up to 36 and top display limit for efficient screening from niche memecoin clusters to full ecosystems
📋 Table Settings
- Background transparency for semi-opaque overlays, ensuring readability while preserving pane context
- Border styling for clear delineation of data sections without visual clutter
- Text sizing options , from compact to prominent, to suit screen preferences and detail levels in dense memecoin grids
📈 RSP Settings
- RSI length for relative strength computations, defining the oscillator period on memecoin cross-ratios
- Primary smoothing type , selectable from standard averages to advanced hull or variable index for signal refinement
- Primary smoothing length , adjusting lag to match analysis timeframe from intraday to weekly
- Secondary smoothing type , allowing layered processing or dynamic comparisons for deeper confirmation
- Secondary smoothing length , providing extended baseline for stable relative momentum readings
- Toggle for second MA comparison , shifting scoring from absolute levels to relative crossovers
- VIDYA volatility lookback , dynamically scaling smoothing to market dispersion for adaptive RSP
🪙 Specific Coins
- ETH symbol input for RSP baseline, anchoring Ethereum memecoin relative strength calculations
- SOL symbol input for Solana ecosystem comparisons, evaluating chain-specific outperformance
- SUI symbol input for SUI memecoin benchmarking, highlighting ecosystem leaders
- VIRTUAL symbol input for BASE/VIRTUAL chain reference, facilitating cross-layer analysis
📊 Ethereum Memecoins
- Individual symbol inputs for up to 9 Ethereum-based memecoins, supporting high-liquidity viral tokens
- Grouped configuration for Ethereum ecosystem focus, enabling chain-specific RSP and metric screening
- Flexible ticker replacement for emerging or favorite memecoins within the Ethereum layer
📊 Solana Memecoins
- Individual symbol inputs for up to 9 Solana-based memecoins, targeting fast-chain speculative plays
- Grouped setup for Solana ecosystem isolation, optimizing relative strength across high-velocity tokens
- Customizable for new Solana launches, integrating with RSP for momentum hierarchy
📊 SUI Memecoins
- Individual symbol inputs for up to 9 SUI-based memecoins, focusing on layer-1 innovation tokens
- Dedicated grouping for SUI chain analysis, facilitating ecosystem-relative performance ranking
- Adaptable for SUI-specific narratives, blending with metrics for targeted selection
📊 BASE/VIRTUAL Memecoins
- Individual symbol inputs for up to 9 BASE/VIRTUAL memecoins, covering emerging layer-2 and virtual assets
- Consolidated group for BASE/VIRTUAL screening, emphasizing cross-layer memecoin dynamics
- Versatile for virtual economy tokens, supporting RSP comparisons within niche categories
📡 Data Fetching
- Benchmark retrieval on demand for alpha or beta needs, using daily resolution for consistent periodicity
- Parallel asset close pulls via security functions for 36 memecoins, ensuring uniform timeframe data
- Specific chain baselines fetched separately for ETH, SOL, SUI, VIRTUAL to enable targeted RSP
- Na defaults for inactive assets, preventing errors in partial memecoin scans
- Confirmed bar gating for price updates, aligning with real-time execution fidelity
🔢 Calculation Functions
- Exchange prefix remover for clean ticker displays, stripping identifiers for concise labeling
- Returns calculator standardizing daily percentage changes, zero-filling gaps for continuity
- Alpha isolator via regression intercept, extracting benchmark-independent performance
- Beta quantifier through covariance ratio, measuring systematic sensitivity with safeguards
- Sharpe efficiency engine , annualizing mean over volatility with exponential noise reduction
- Sortino downside protector , looping negative deviations for targeted risk adjustment and scaling
- Omega distribution analyzer , accumulating excesses and shortfalls for gain-loss probability ratios
- ROC momentum extractor , delivering unbounded percentage shifts with na neutrality
- Constant source checker , filtering static data to avoid misleading RSP computations
- Smoothed RSI calculator , applying multi-type averages including volatility-responsive VIDYA
- Score generator , binary outcomes from level thresholds or MA crossovers on relative prices
- RSP scores calculator , aggregating binaries across chain baselines for ecosystem leadership
📊 Returns Calculations
- Daily returns series for all 36 memecoins, foundational for regression and ratio inputs
- Benchmark returns computed conditionally, serving as relative analysis baseline
📈 Alpha Calculations
- Per-memecoin alpha toggled and derived, isolating benchmark excess for speculative edge detection
- Regression-based intercepts across assets, feeding into binary outperformance flags
📈 Beta Calculations
- Per-memecoin beta activated on demand, quantifying chain volatility against market
- Covariance ratios for systematic exposure, enhancing risk context in memecoin rankings
⚖️ Sharpe Calculations
- Rolling annualized Sharpe for each memecoin, assessing efficiency in high-volatility plays
- Smoothed volatility-adjusted returns , parallel computation for cross-chain comparability
🛡️ Sortino Calculations
- Downside-focused Sortino [/b> per memecoin, emphasizing loss aversion in speculative assets
- Loop-based deviation summing [/b>, scaled annually with risk-free adjustment for precision
🔄 Omega Calculations
- Distributional omega for each memecoin, capturing tail risks in viral surges
- Target-threshold accumulation [/b>, smoothed for gain-loss probability insights
📉 ROC Calculations
- Momentum ROC [/b> across memecoins, unbounded percentage changes for trend velocity
- Period-specific extraction , toggled for short-term hype detection
🏆 RSP Calculations
- Price array storage for 36 memecoins, enabling relative ratio computations
- Per-asset RSP matrices [/b>, filling with smoothed RSI binaries on cross-memecoin ratios
- Grand combined array [/b>, flattening matrices for holistic rank derivation
- Summed totals per asset , aggregating RSP strengths for competitive positioning
🪙 Specific RSP Scores
- Chain baseline prices for ETH, SOL, SUI, VIRTUAL, anchoring ecosystem-relative computations
- 4-coin RSP scoring , generating binaries on cross-chain ratios for leadership identification
- Max score indexing , pinpointing the dominant chain for category-wide RSP4 flags
📊 Median & Binary Scores
- Enabled metric arrays , collecting valid values for central tendency computation
- Median extraction per metric, providing neutral benchmarks for outperformance flags
- Binary conversion loops , flagging above-median as positive for normalized scoring
- Na exclusion , ensuring only reliable data influences relative classifications
- Per-asset binary arrays , storing flags for weighted contribution to final composites
- RSP4 category flags , binary boosts for memecoins in the leading chain group
🎯 Weighted Scores
- Metric binary summation , averaging enabled flags for risk-return consensus
- RSP points integration , blending rank rewards with metric outcomes for hybrid intelligence
- RSP4 category addition , elevating scores for ecosystem-dominant memecoins
- Balanced weighting , allocating portions to metrics and RSP for multifaceted evaluation
- Last-bar computation , finalizing scores for display without historical interference
📋 Main Data Table
- 16-column matrix centering memecoins with RSP scores, metrics, binaries, RSP4, and final scores
- Header labeling [/b> for clarity, spanning asset identifiers, RSP, performance columns, and flags
- Value rendering , formatted decimals or dashes for unavailable metrics
- Binary color-coding , green for above-median, red below, gray for invalids
- RSP score highlighting , green/red based on positive outperformance
- RSP4 flag column , green for chain leaders, red otherwise
- Score culmination , white text on transparent cells for final eligibility gauge
- Text sizing [/b> uniformity, ensuring legibility in expanded memecoin grids
📊 Median Table
- Compact right-side panel , listing medians for enabled metrics as reference anchors
- Two-column simplicity , metric names left, values right for quick benchmarking
- Dash placeholders [/b> for inactive metrics, maintaining structure without clutter
- White text consistency , neutral presentation for objective central tendencies
🏆 Top Assets Table
- Left-side summary , ranking memecoin leaders by weighted scores in descending order
- Two-column focus , tickers paired with scores for executive overview
- Dynamic sorting [/b> via indices, limiting to top count for prioritized insights
- Prefix-cleaned names , concise labels enhancing scan speed across chains
- Decimal score formatting , white text for clean highlight of elite memecoins
✅ Key Takeaways
- Chain-segmented RSP [/b> uncovers memecoin leaders within Ethereum, Solana, SUI, and BASE/VIRTUAL ecosystems
- Category RSP4 flags boost scores for dominant chain performers, emphasizing viral potential
- Expanded 36-asset capacity scales screening for comprehensive memecoin universes
- Tiered tables [/b>—detailed main with RSP4, neutral medians, elite tops—streamline from scan to speculation
- Modular toggles and smoothings adapt to memecoin volatility, from hype cycles to corrections
- Rank rewards incentivize competitive RSP, revealing cross-chain alpha in speculative niches
- Daily alignment ensures timely insights, quota-efficient for high-volume memecoin tracking
AssetIQ -> PROFABIGHI_CAPITAL🌟 Overview
The AssetIQ -> PROFABIGHI_CAPITAL indicator is an advanced multi-asset intelligence tool for cryptocurrency analysis, blending traditional risk-adjusted metrics with relative strength positioning (RSP) via RSI on cross-asset price ratios to compute comprehensive eligibility scores. It evaluates up to 25 assets against a benchmark, generating weighted composites from binary outperformance flags and rank-based points, displayed in detailed tables for median comparisons and top rankings to guide portfolio selection in competitive markets.
📅 General Settings
- Toggle for activating alpha to isolate excess returns beyond benchmark influence, highlighting unique asset drivers
- Toggle for enabling beta to quantify volatility correlation with the benchmark, aiding diversification assessments
- Toggle for incorporating Sharpe ratio to gauge overall efficiency of returns relative to total risk exposure
- Toggle for including Sortino ratio to prioritize returns adjusted specifically for downside volatility impacts
- Toggle for utilizing omega ratio to weigh probability-adjusted gains against losses above a target threshold
- Toggle for adding rate of change (ROC) to capture raw momentum shifts over a specified horizon
- Adjustable lookback periods for alpha and beta regressions, tuning between stability and recency in relative analysis
- Customizable benchmark symbol , such as market indices, to establish the reference frame for comparative evaluations
- Configurable Sharpe rolling window and smoothing for responsive risk-reward snapshots
- Extended Sortino and omega periods with risk-free rates and target returns for robust downside and distributional insights
- ROC horizon setting to balance short-term reactivity with trend confirmation
- Scalable asset count and top display limit for efficient screening from watchlists to full universes
📋 Table Settings
- Background transparency for semi-opaque overlays, ensuring readability while preserving chart context
- Border styling for clear delineation of data sections without visual clutter
- Text sizing options , from compact to prominent, to suit screen preferences and detail levels
🏷️ Ticker Settings
- Dedicated inputs for up to 25 cryptocurrency symbols, supporting major pairs across exchanges for broad coverage
- Flexible symbol formatting with prefix handling, enabling seamless integration of diverse tickers
- Conditional loading based on asset count, optimizing data retrieval for selected instruments only
📈 RSP Settings
- RSI length for relative strength computations, defining the oscillator period on cross-asset ratios
- Primary smoothing type , selectable from standard averages to advanced hull or variable index for signal refinement
- Primary smoothing length , adjusting lag to match analysis timeframe from intraday to weekly
- Secondary smoothing type , allowing layered processing or dynamic comparisons for deeper confirmation
- Secondary smoothing length , providing extended baseline for stable relative momentum readings
- Toggle for second MA comparison , shifting scoring from absolute levels to relative crossovers
- VIDYA volatility lookback , dynamically scaling smoothing to market dispersion for adaptive RSP
📡 Data Fetching
- Benchmark retrieval on demand for alpha or beta needs, using daily resolution for consistent periodicity
- Parallel asset close pulls via security functions, ensuring uniform timeframe data across symbols
- Na defaults for inactive assets, preventing errors in partial portfolio scans
- Confirmed bar gating for price updates, aligning with real-time execution fidelity
🔧 Core Functions
- Exchange prefix remover for clean ticker displays, stripping identifiers for concise labeling
- Returns calculator standardizing daily percentage changes, zero-filling gaps for continuity
- Alpha isolator via regression intercept, extracting benchmark-independent performance
- Beta quantifier through covariance ratio, measuring systematic sensitivity with safeguards
- Sharpe efficiency engine , annualizing mean over volatility with exponential noise reduction
- Sortino downside protector , looping negative deviations for targeted risk adjustment and scaling
- Omega distribution analyzer , accumulating excesses and shortfalls for gain-loss probability ratios
- ROC momentum extractor , delivering unbounded percentage shifts with na neutrality
📈 RSP Functions
- Constant source checker , filtering static data to avoid misleading RSP computations
- Smoothed RSI calculator , applying multi-type averages including volatility-responsive VIDYA
- Score generator , binary outcomes from level thresholds or MA crossovers on relative prices
- Array population routine , filling per-asset matrices with RSP binaries for cross-comparisons
- Combined matrix builder , concatenating RSP arrays into a unified grid for rank derivation
- Rank-based points assigner , scaling rewards from top positions to encourage competitive outperformance
📊 Calculations
- Daily returns series for all assets, foundational for regression and ratio inputs
- Per-asset alpha and beta toggled and computed, feeding relative strength arrays
- Sharpe, Sortino, omega, and ROC parallels, with na handling for robust aggregation
- RSP price arrays , storing historical closes for ratio-based RSI evaluations
- Per-asset RSP matrices , computing smoothed oscillators on relative pricing
- Summed RSP totals , aggregating binary strengths for initial rank seeding
📦 RSP Calculations
- Asset price fetching on confirmed bars, populating arrays for relative computations
- Matrix filling loops , applying RSP scoring across all active asset pairs
- Grand combined array , merging matrices into a flat structure for efficient ranking
- Per-asset sum arrays , totaling RSP strengths to establish competitive hierarchies
- Rank derivation , comparing sums to assign positions from leader to laggard
- Points scaling , tiered rewards diminishing from top ranks to foster differentiation
📊 Median & Binary
- Enabled metric arrays , collecting valid values for central tendency computation
- Median extraction per metric, providing neutral benchmarks for outperformance flags
- Binary conversion loops , flagging above-median as positive for normalized scoring
- Na exclusion , ensuring only reliable data influences relative classifications
- Per-asset binary arrays , storing flags for weighted contribution to final composites
⚖️ Weighted Scores
- Metric binary summation , averaging enabled flags for risk-return consensus
- RSP points integration , blending rank rewards with metric outcomes for hybrid intelligence
- Balanced weighting , allocating portions to metrics and RSP for multifaceted evaluation
- Last-bar computation , finalizing scores for display without historical interference
📋 Main Table Display
- 16-column matrix centering assets with metric values, binaries, ranks, points, and scores
- Header labeling [/b> for clarity, spanning asset identifiers and performance columns
- Value rendering [/b>, formatted decimals or dashes for unavailable metrics
- Binary color-coding , green for above-median, red below, gray for invalids
- Rank and points [/b> in dedicated columns, highlighting competitive positioning
- Score culmination [/b>, white text on transparent cells for final eligibility gauge
- Text sizing [/b> uniformity, ensuring legibility in dense layouts
📊 Median Table
- Compact right-side panel [/b>, listing medians for enabled metrics as reference anchors
- Two-column simplicity , metric names left, values right for quick benchmarking
- Dash placeholders [/b> for inactive metrics, maintaining structure without clutter
- White text consistency [/b>, neutral presentation for objective central tendencies
🏆 Top Assets Table
- Left-side summary [/b>, ranking leaders by weighted scores in descending order
- Two-column focus [/b>, tickers paired with scores for executive overview
- Dynamic sorting [/b> via indices, limiting to top count for prioritized insights
- Prefix-cleaned names [/b>, concise labels enhancing scan speed
- Decimal score formatting [/b>, white text for clean highlight of elite performers
✅ Key Takeaways
- Hybrid RSP integration [/b> elevates traditional metrics with cross-asset relative strength for superior selection
- Binary medians [/b> normalize outperformance, creating fair comparisons across diverse assets
- Weighted composites fuse risk, momentum, and positioning into actionable intelligence
- Tiered tables [/b>—detailed main, neutral medians, elite tops—streamline from scan to strategy
- Modular toggles and smoothings adapt to regimes, from bull hunts to bear shields
- Rank rewards incentivize competitive RSP, uncovering hidden portfolio alphas
- Daily alignment [/b> ensures timely insights, scalable for watchlists or full scans
💸 Monetary Momentum Oscillator (MMO)Monetary Momentum Oscillator (MMO)
The Monetary Momentum Oscillator (MMO) measures the rate of change in the money supply (like M2, Fed Balance Sheet, or similar macro series) and applies a momentum-based RSI calculation to visualize liquidity acceleration and deceleration.
💡 Purpose:
MMO is designed for macro-level analysis — it identifies when monetary expansion is overheating (potential inflation or risk-on conditions) and when contraction is cooling off (liquidity tightening or deflationary stress).
📊 How It Works:
Calculates the percentage change of the selected data source over a chosen lookback period.
Applies an RSI transformation to visualize momentum extremes.
Overlays signal smoothing and highlights overheat/cooldown zones.
🔍 Interpretation:
Above 70 → Liquidity acceleration / overheating (potential inflationary impulse).
Below 30 → Liquidity deceleration / contraction (risk-off, tightening).
Crossovers → Momentum shifts that often precede macro trend reversals in risk assets.
⚙️ Best Used On:
Macroeconomic series such as M2SL, M2V, WALCL, or custom liquidity indexes.
Long-term charts (weekly or monthly) for detecting major monetary regime transitions.
🧩 Core Idea:
Liquidity is the real market engine — this oscillator quantifies its pulse.
ICT Killzones & MacrosICT Killzones & Macros (v1.1.5) — configurable ICT session windows + refined “macro” windows with live High/Low levels, optional extensions, next-window previews, and lightweight opening-price lines. Built to be clock-robust, timezone-aware, and performant on intraday charts.
Tip: All times are interpreted in your chosen IANA timezone (default: America/New_York) and auto-handle DST. You can rename, recolor, enable/disable, and retime every window.
What it plots
- Killzones (5) : Asia (19:00–02:00), London (02:00–05:00), NY AM (07:00–09:30), London Close (10:00–12:00), NY PM (13:30–16:00) — full-height boxes with optional header.
- Macros (8) (defaults tailored for common ICT “refined” windows): Asia-1 (18:00–21:00), Asia-2 (21:00–00:00), London-1 (01:00–04:00), AM-1 (09:45–10:15), AM-2 (10:45–11:15), Lunch (12:00–13:00), PM-1 (13:30–14:30), Power Hour (15:10–16:00).
- Live High/Low lines for the current Macro/Killzone window.
- Optional HL extension to the right until price crosses or the trading day rolls (style selectable).
- “Next” previews : earliest upcoming Macro and Killzone header; optional next-window background band.
- Opening Prices (3 lightweight time lines) : defaults 00:00, 08:30, 09:30 with right-edge labels, scoped to a session you choose (auto-cleans at session end).
- Key inputs & styling
- General : Timezone (IANA), “Sessions to show” (per window) to keep only the last N completed windows.
- Header : height (ticks), gap (ticks), fill opacity, border width/style, text size/color, toggle “Next Macro/Killzone” headers.
- Boxes : global fill opacity, global border width/style (used by both Macros & Killzones).
- High/Low : show HL, HL line style, extend on/off + extension style, optional extension labels.
- Opening Prices : enable Time 1/2/3, set HH:MM for each, session window, per-line colors, style (dotted/dashed/solid), width.
- Per-window controls : each Macro/Killzone has Enable, Session (HHMM-HHMM), Label, Fill color.
How to use (quick start)
- Set Timezone to your preference (default America/New_York).
- Toggle on the Macros and Killzones you trade. Adjust session times if needed.
- (Optional) Turn on Extend High/Low to project levels until crossed/day-roll.
- (Optional) Enable Next… headers to see the next upcoming window at a glance.
- (Optional) Configure Opening Prices (00:00 / 08:30 / 09:30 by default) and the session over which they appear.
Behavior & notes
- Time windows are computed by clock, not by guessing bar timestamps, making them robust across brokers and timeframes.
- With HL extension on, the current window’s levels extend until crossed or the end of the trading day (in your timezone). With it off, completed windows keep static HL markers (limited by “Sessions to show”).
- “Sessions to show” applies per Macro/Killzone to automatically prune older windows and keep charts snappy.
- Opening-price lines exist only within the chosen “Opening Prices Session” and are removed when it ends (keeps charts clean).
Defaults (color cues)
Killzones: Asia (blue), London (purple), NY AM (green), London Close (yellow), NY PM (orange).
Macros: neutral greys with Lunch and PM accents out of the box (all customizable).
Performance tips
- Reduce “Sessions to show” if you scroll far back in history.
- Disable “Next…” previews and/or extension labels on very slow machines.
- Narrow the “Opening Prices Session” window to exactly when you need those lines.
Changelog highlights
- v1.1.5 : Internal refinements and stability.
- v1.1.3 : Live High/Low lines for current windows + optional extension.
- v1.1.2 : Added “next Killzone” preview (to match “next Macro”).
- v1.1.0 : Defaults updated (5 KZ, 8 Macros). Removed “snap-to-killzone” behavior.
- v1.0.0 : Independent Macro vs. Killzone rendering; cleaner header logic.
- Known limitations
If your chart warns about drawings, trim “Sessions to show”.
If your broker session times differ from NY hours, adjust the sessions or change the indicator timezone.
Credits & intent
Inspired by ICT timing concepts; provided for education/mark-up, not financial advice.
Built to be flexible so you can mirror your personal playbook and journaling workflow.
The Eligible Asset Power Table -> PROFABIGHI_CAPITAL🌟 Overview
The Eligible Asset Power Table is a multi-asset screening dashboard that assesses cryptocurrency portfolios across multiple momentum, risk, and relative metrics to generate eligibility scores. It combines RSI variants, rate of change layers, Sharpe ratios, momentum RSI, price delta analysis, and beta exposure to rank assets, helping traders identify high-conviction opportunities through dual-mode scoring and visual tables.
⚙️ General Settings
- Evaluation mode toggle between aggressive averaging for nuanced scoring or conservative consensus requiring all conditions met for full eligibility
- Number of assets to screen, adjustable up to the platform's data fetch limits for focused or comprehensive portfolio reviews
- Count of top-ranked assets for a dedicated summary table, customizable to highlight leading candidates without overwhelming the display
📊 Indicator Parameters - RSI#1
- Source price selection for RSI input, allowing adaptation to closes, highs, or other series for tailored momentum sensitivity
- Period length for the shorter RSI variant, tuning detection of near-term overbought or oversold zones
- Primary smoothing moving average type, from basic to advanced options like hull or variable index for refined signal clarity
- Length for the first smoothing layer, balancing lag and responsiveness in volatile conditions
- Secondary smoothing moving average type, enabling dual-layer processing or crossover comparisons for added confirmation
- Length for the second smoothing layer, providing deeper trend stability
- Toggle for second MA comparison mode, shifting from fixed thresholds to dynamic relative movements
- Volatility lookback for adaptive smoothing when using variable index methods, responding to market dispersion
📊 Indicator Parameters - RSI#2
- Period length for the medium-term RSI variant, capturing sustained momentum beyond immediate fluctuations
- Primary smoothing moving average type applied to the longer RSI, consistent with RSI#1 for uniform processing
- Length for the first RSI#2 smoothing, optimizing for intermediate trend persistence
- Secondary smoothing moving average type, supporting layered refinement or bullish/bearish crossovers
- Length for the second RSI#2 smoothing, enhancing equilibrium zone reliability
- Toggle for second MA comparison, favoring motion-based conditions over static levels
- Volatility lookback specific to RSI#2's adaptive smoothing, scaling to regime changes
📈 Indicator Parameters - ROC#1
- Period length for the shortest rate of change, emphasizing immediate price acceleration for quick trend shifts
📈 Indicator Parameters - ROC#2
- Period length for the medium rate of change, evaluating ongoing momentum to validate directional strength
📈 Indicator Parameters - ROC#3
- Period length for the longest rate of change, assessing extended trends to confirm multi-period alignment
⚡ Indicator Parameters - Sharpe Ratio
- Lookback period for return averaging and volatility measurement, defining the window for efficiency snapshots
- Smoothing period on raw ratios, applying exponential decay to highlight persistent risk-reward patterns
- Buy threshold for positive conditions, establishing the minimum efficiency level for asset qualification
- Sell threshold for negative flags in averaging mode, pinpointing low-efficiency underperformers
🎯 Momentum RSI Parameters
- Momentum input period, deriving price changes to feed into RSI for velocity-driven insights
- RSI period on the momentum series, normalizing changes into overbought/oversold signals
- Primary smoothing moving average type on momentum RSI, selectable for signal purification
- Length for the first momentum RSI smoothing, aligning lag with trading horizons
- Secondary smoothing moving average type, facilitating comparative layers for crossover setups
- Length for the second momentum RSI smoothing, adding baseline robustness
- Toggle for second MA comparison, prioritizing relative dynamics over absolute readings
- Volatility lookback for momentum RSI's adaptive smoothing, attuning to velocity dispersion
📊 Indicator Parameters - Price Delta RSI
- Condition type between raw delta or RSI-transformed, choosing direct flow analysis or oscillator normalization
- Period for price delta calculation, quantifying net changes to reveal underlying pressure
- RSI period applied to delta, smoothing flow into bounded momentum readings
- Primary smoothing type for delta RSI, from averages to hull for delta refinement
- Length for the first delta RSI smoothing, tuning to flow trends in ranging or trending phases
- Secondary smoothing type, enabling dual-MA for enhanced crossover precision
- Length for the second delta RSI smoothing, bolstering signal stability
- Toggle for second MA comparison on delta RSI, emphasizing motion over static hurdles
- Volatility lookback for delta RSI's adaptive smoothing, adapting to flow-specific variability
📉 Beta Parameters
- Benchmark symbol choice, such as market indices, to gauge asset sensitivity against broader movements
- Lookback period for beta estimation, ensuring sufficient data for covariance while staying current
💼 Assets Configuration
- Sequential symbol inputs for up to 39 assets, supporting diverse crypto pairs across exchanges
- Conditional data loading by count, activating fetches only for selected instruments to conserve resources
- Prefix handling for clean display, stripping exchange details for ticker focus
- Broad compatibility for majors, mid-caps, or niche tokens, enabling sector or theme-based scans
🔧 Helper Functions
- Versatile moving average applicator, supporting multiple types including exponential variants and volatility-adjusted for flexible smoothing
- Sharpe ratio engine, annualizing mean returns over volatility with optional decay for trend focus
- Beta regressor, pulling benchmark data to compute relative risk via return covariances
- Layered ROC calculators, delivering percentage changes across horizons for momentum stacking
📊 Indicator Calculations
- Dual RSI systems with multi-MA options, scoring on optimal ranges or crossover confirmations for balanced strength
- Triple ROC cascade from acute to chronic, binary scoring on positivity to align short, medium, and long trends
- Sharpe derivation prioritizing excess efficiency, with thresholds gating high-reward low-risk assets
- Momentum RSI fusing velocity into RSI, smoothed for level or motion-based bullish filters
- Price delta probing net flow, raw or RSI-normalized, with adaptive layers for directional purity
- Beta isolating systematic exposure, supplementing scores with market-context relativity
🎯 Asset Metrics Calculation
- Parallel per-asset pipeline fetching and computing metrics, unpacking into arrays for centralized handling
- Binary condition evaluation per indicator: thresholds, crossovers, or signs, feeding into mode-specific aggregation
- Eight-metric blend: RSIs, ROCs, Sharpe, momentum RSI, delta, averaged aggressively or unanimous conservatively
- Beta as orthogonal factor, weighting top ranks without score dilution
- Neutral na defaults, preserving evaluations amid data gaps
📦 Data Storage Arrays
- Fixed-size arrays for names, metrics, conditions, and flags, indexed by asset order for efficient access
- Segregated storage for raw values, binaries, and composites, supporting sorting and retrieval
- Scalable to max assets, minimizing overhead in partial loads
📊 Data Retrieval for All Assets
- Conditional security pulls aligned to chart timeframe, ensuring consistent multi-symbol data
- Metrics function per instrument, distributing results to arrays for unified processing
- Benchmark-embedded beta calls, avoiding extra fetches
- Last-bar gating for snapshot accuracy, sidestepping repaints
📊 Main Table for All Assets
- Centered wide-format table listing assets leftward with metric columns spanning conditions and beta
- Headers labeling RSI layers, ROC trio, Sharpe, momentum, delta, beta, and final score for metric traceability
- Green/red cell text for met/failed conditions, white neutrals, with score highlighting above midpoint
- Ticker truncation for compactness, transparent overlay for pane integration
🏆 Top Assets Table
- Left-aligned rankings by score-beta composite, descending to prioritize leaders
- Compact four-column view: ticker, score, beta, Sharpe with threshold colors for efficiency triage
- Temporary key sorting, row clearing for updates, limited to user count
- Visual cues mirroring main table, flagging high-Sharpe standouts
✅ Key Takeaways
- Fuses diverse metrics into probabilistic or strict eligibility for alpha hunting across assets
- Dual modes adapt screening from flexible averages to rigorous confluences
- Custom periods and smoothings tune to timeframes, from scalps to positions
- Dual tables balance detail with digestible summaries for rapid insights
- Beta adds relativity, elevating resilient picks in correlated markets
- Efficient array handling scales screening without lag, quota-aware
PROFABIGHI_CAPITAL Ratio🌟 Overview
The PROFABIGHI_CAPITAL Ratio Tracker is a comprehensive multi-asset performance dashboard designed for cryptocurrency portfolio analysis , evaluating up to 33 altcoins against a customizable benchmark using six key quantitative metrics: alpha for excess returns, beta for relative volatility, Sharpe ratio for overall risk-adjusted performance, Sortino ratio for downside risk focus, omega ratio for probability-weighted gain-loss assessment, and rate of change (ROC) for momentum tracking. It aggregates these metrics into unified composite scores for each asset, enabling traders to rank and compare opportunities through intuitive table-based visualizations , median benchmarking , and top-performer highlights , all while supporting selective metric activation, adjustable parameters, and real-time alerts for systematic decision-making in volatile markets.
⚙️ Metrics Selection
- Toggle for enabling alpha calculations to quantify an asset's unique performance beyond benchmark movements , ideal for identifying true outperformance in diversified portfolios
- Toggle for activating beta measurements to evaluate how closely an asset mirrors benchmark volatility , helping assess diversification benefits or leverage exposure
- Toggle for incorporating Sharpe ratio to measure returns per unit of total risk , providing a standardized benchmark for comparing asset efficiency across varying volatility profiles
- Toggle for including Sortino ratio to emphasize returns adjusted for harmful downside moves only, particularly useful in asymmetric markets like crypto where upside swings are desirable
- Toggle for utilizing omega ratio to analyze the full return distribution by weighting probable gains against losses relative to a target threshold , capturing tail risks and skewness effects
- Toggle for adding rate of change to capture short-term momentum trends , complementing longer-term risk metrics with directional conviction signals
- Modular activation allows traders to tailor the analysis to specific philosophies, such as risk-averse setups focusing on Sortino and omega or momentum-driven approaches emphasizing ROC alongside Sharpe
- Computational efficiency through conditional enabling, ensuring only selected metrics consume resources while maintaining flexibility for evolving market conditions or strategy refinements
🎯 Alpha and Beta Parameters
- Adjustable lookback period for alpha and beta computations, balancing statistical robustness with responsiveness —longer horizons smooth noise for stable estimates, shorter ones highlight recent regime shifts
- Customizable benchmark symbol selection, such as broad market cap indices or sector-specific aggregates , to define the reference for relative performance evaluation and ensure meaningful comparisons
- Alpha derivation as the intercept in a regression of asset returns against benchmark returns , revealing skill-based outperformance after accounting for systematic market exposure
- Beta estimation via covariance divided by benchmark variance , quantifying sensitivity to market moves —values above 1 signal amplified volatility for growth-oriented allocations , below 1 indicate defensive traits
- Shared lookback application across both metrics for consistency, with higher values promoting trend-following reliability and lower values enabling tactical adjustments to intraday or weekly dynamics
- Conditional benchmark data fetching only when alpha or beta is active, optimizing script performance by avoiding unnecessary external data requests in lightweight configurations
- Tooltip-guided parameter explanations emphasizing trade-offs between smoothness and reactivity, aiding users in aligning settings with their timeframe and risk tolerance
- Integration with daily return series for precise regression inputs, ensuring calculations reflect realistic percentage-based movements rather than absolute price changes
⚡ Sharpe Ratio Parameters
- Rolling period for mean return and volatility estimation , where shorter windows capture recent performance spikes for agile monitoring, and longer ones provide trend-stable assessments
- Exponential moving average smoothing length to filter daily fluctuations in raw ratios, reducing visual noise while preserving signals of genuine risk-return shifts
- Daily return computation via price changes divided by prior close , standardizing inputs for cross-asset comparability regardless of nominal price levels
- Mean return via simple moving average over the period, representing average daily excess as the reward component in the risk-adjusted formula
- Standard deviation of returns as the risk denominator , capturing total volatility including both upside and downside deviations for holistic efficiency gauging
- Raw ratio as mean divided by standard deviation , with zero-volatility safeguards to prevent errors during flat periods , defaulting to neutral performance
- Annualization through multiplication by the square root of 365 , converting daily metrics to yearly equivalents for intuitive benchmarking against industry standards
- Smoothed and annualized output for each asset, enabling direct ranking of risk efficiency —higher values highlight superior return generation per volatility unit
🎯 Sortino Ratio Parameters
- Extended lookback for downside deviation accumulation , favoring longer periods for reliable negative return sampling in sporadic drawdown environments
- Annual risk-free rate input as the downside threshold , adjustable to reflect opportunity costs like bond yields or inflation , with zero default treating all losses as harmful
- Smoothing period via EMA to stabilize the ratio against window shifts , mirroring Sharpe approach but tailored to the selective nature of downside focus
- Periodic returns calculated as close-to-prior ratios minus one, ensuring percentage consistency for multi-asset analysis
- Effective period adaptation to available bars, allowing early calculations with shorter windows that expand over time for progressive accuracy
- Downside squared deviations summed only for underperformance instances , divided by period count , then square-rooted for standard deviation equivalent
- Raw ratio as excess mean return over downside deviation , scaled annually via square root scaling , emphasizing protection against capital erosion
- Smoothed final values per asset, rewarding strategies that minimize harmful volatility while ignoring beneficial upside dispersion common in crypto rallies
🔄 Omega Ratio Parameters
- Calculation period for return distribution sampling , longer horizons capturing fuller gain-loss spectra for robust probability weighting
- Target return threshold per period, defining success boundaries —zero treats positives as gains , positives add hurdles for conservative analysis
- EMA smoothing to dampen ratio swings from individual extreme returns entering or exiting the window, maintaining trend clarity
- Periodic returns derived similarly to other ratios, with decimal conversion of target for precise excess/shortfall computations
- Cumulative above-target excesses summed for gains , below-target shortfalls for losses , via explicit loop over historical series
- Raw ratio as gains divided by losses , with zero-loss default to neutral rather than infinity, avoiding misleading perfect-period artifacts
- Smoothed output revealing distributional health —ratios above 1 favor gains , higher values signal skewed positives ideal for tail-risk hedging
- Asset-specific computations highlighting asymmetry , where fat positive tails in crypto assets can elevate omegas despite high total volatility
📈 Rate of Change Parameters
- Period length for percentage momentum measurement , shorter for reactive trend detection , longer for sustained direction confirmation
- Built-in ROC function application to source prices , yielding unbounded percentage shifts —positive for uptrends , negative for downtrends
- Zero default for missing data , treating data gaps as neutral momentum to avoid biasing composite scores
- Complementary role to risk metrics , capturing raw directional strength without normalization, spotlighting acceleration phases
- Direct integration into averages, where high ROC boosts scores in momentum-favoring selections , balanced by volatility adjustments elsewhere
- Simplicity in computation enabling lightweight inclusion , with na handling ensuring seamless array pushes in scoring logic
💼 Assets Configuration
- Number of altcoins to monitor and display, scalable from focused portfolios to broad market scans for comprehensive opportunity hunting
- Top combined assets count for dedicated ranking table , adjustable to highlight elite performers without overwhelming the view
- Individual symbol inputs grouped left and right for organizational clarity , accepting crypto pairs , indices , or custom tickers
- Conditional activation based on total count , loading only selected assets to optimize data requests and calculations
- Default focus on major and mid-cap altcoins , but fully customizable for sector-specific or emerging token universes
- Prefix stripping in displays for clean ticker presentation , enhancing readability in table formats
- Array-based storage of names and scores post-calculation, facilitating sorting , medians , and iterative population
- Integration with security requests for daily closes , ensuring uniform timeframe data across diverse exchanges
🎨 Table Style
- Background color with transparency for semi-opaque overlays , blending professional aesthetics with chart visibility
- Border color for frame delineation , providing subtle separation without distracting from metric focus
- Consistent application across main , median , and top tables , maintaining visual coherence in multi-panel layouts
- Frame width and color for structural emphasis , using dark tones to evoke institutional-grade presentation
- Color functions for score backgrounds — green for above-median outperformance , red for underperformance , gray for invalids
- Emoji integration for intuitive cues — rockets for strong assets , down arrows for laggards , enhancing at-a-glance scanning
📡 Data Fetching and Returns Calculation
- Benchmark close retrieval conditional on alpha or beta needs, using daily timeframe for consistent periodicity
- Parallel asset close fetches via security calls , defaulting to na for inactive symbols to prevent errors
- Returns function standardizing one-period ROC for daily percentage changes , zero-filling na for continuity
- Benchmark returns computed similarly, serving as regression baseline for relative metrics
- Na propagation to individual asset returns , ensuring downstream calculations skip invalid data gracefully
- Daily resolution enforcement across all fetches, aligning with annualization assumptions in ratios
- Efficient conditional logic minimizing API calls , scalable to full 33-asset loads without performance degradation
📈 Alpha Calculation
- Function guarding against na inputs , returning na for insufficient data to flag unreliable estimates
- Mean asset and benchmark returns via SMA over lookback , establishing central tendencies
- Covariance as product mean minus means product , capturing joint variability
- Benchmark variance similarly, ensuring positive denominator for beta
- Beta as cov/var ratio , zero-default for flat benchmarks to avoid divisions
- Alpha as asset mean minus beta times benchmark mean , isolating idiosyncratic performance
- Zero fallback for na alphas , treating computation failures as neutral in composites
- Per-asset execution only when enabled, feeding into scoring arrays for holistic aggregation
📉 Beta Calculation
- Identical input guards and mean computations as alpha , leveraging shared regression framework
- Covariance and variance derivations mirroring alpha prep , focusing solely on slope coefficient
- Beta output as sensitivity measure , with zero handling for degenerate cases
- Na-to-zero conversion for seamless array integration , avoiding score distortions
- Toggle-based activation per asset, allowing isolated volatility analysis without excess return overhead
- Conceptual role in diversification —low betas signal hedges , high ones amplify market bets
- Lookback sensitivity trade-off : short for tactical betas , long for structural exposures
⚡ Sharpe Ratio Calculation
- Source na guard returning na , preserving data integrity
- Daily returns via change over prior source , avoiding log approximations for arithmetic consistency
- Period SMA for mean reward , stdev for total risk dispersion
- Raw daily ratio with zero-stdev neutral default , preventing infinities
- Nz-EMA smoothing to dampen variability , weighting recent ratios heavily
- Sqrt(365) annualization for yearly comparability , assuming i.i.d. returns
- Zero na fallback , distinguishing errors from flat performance
- Asset-parallel computations , ranking efficiency where high Sharpes indicate optimal risk pricing
🎯 Sortino Ratio Calculation
- Na source guard , with annualization factor predefined for scaling
- Periodic returns and per-period risk-free derivation for threshold alignment
- Effective period min with bar count , enabling progressive buildup
- Loop-summed downside squares only for positive deviations ( underperformance ), averaged and sqrt-ed
- Excess mean over downside dev , scaled annually , zero-dev neutral
- Nz-EMA smoothing for stability , focusing on loss aversion
- Zero na output , emphasizing downside protection in crypto's crash-prone nature
- Longer periods favored for sparse downside events , enhancing estimate reliability
🔄 Omega Ratio Calculation
- Na guard with periodic returns and decimal target setup
- Loop over period accumulating above-target excesses vs. below shortfalls
- Raw ratio as gains/losses , zero-loss neutral to conservatism
- Nz-EMA smoothing , defaulting raw na to zero for continuity
- Distributional insight : >1 favors assets with skewed positives , <1 warns of loss dominance
- Target flexibility —zero for absolute , positive for relative hurdles
- Per-asset loops ensuring full history scan , capturing crypto's lottery-like tails
📈 Rate of Change Calculation
- Simple ta.roc application over period , percentage momentum direct from prices
- Na-to-zero for gaps , neutral in momentum absence
- Unbounded output allowing extreme trend magnitudes , unlike bounded oscillators
- Toggle integration boosting composites in trending selections
- Short-period reactivity for entry timing , complementing ratio stability
🎯 Combined Score Calculation
- Selected metrics count via incremental ifs , normalizing averages
- Last-bar loop over assets , building per-asset score arrays
- Switch-retrieved metric values , na-filtered pushes with valid count tracking
- Average only over valid scores , handling partial data gracefully
- Var assignment to per-asset combined vars , persisting for table use
- Equal-weighting assumption , treating metrics as complementary signals
- Na results when no valids , flagging data-deficient assets
- Holistic aggregation simplifying multi-metric overload into rankable scores
📊 Table Display Functions
- Background color getter : green above median , red below, gray invalid
- Emoji selector : rocket for outperformers , down for underperformers , blank invalid
- Row/column math for three-column layout , maximizing space efficiency
- Prefix-stripped asset names for compact display
- Rounded three-decimal scores or N/A , centered alignment
- Header branding centered, dark background for prominence
- Median table compact right-side , gray neutral for reference
- Top table left-side descending sort via indices array , limited rows
📋 Table Preparation
- Var arrays for names and scores , last-bar conditional pushes
- Conditional per-asset adds based on num_assets , avoiding over-allocation
- Median via array.median , central tendency for relative gauging
- Sort indices descending for top ranking , min with size for bounds
- String concatenation for alerts , newline-separated asset-score pairs
- Once-per-bar alert freq , compiling only non-na for actionable output
- Barstate.islast gating all prep/display , preventing historical repaints
✅ Key Takeaways
- Modular metrics enable tailored risk-return portfolios , from alpha hunts to downside shields
- Composite scores distill complexity into actionable rankings , median-anchored for relativity
- Benchmark-relative analysis uncovers crypto alphas amid market noise
- Table triad — main matrix , median ref , top highlights —delivers scannable insights
- Alerts and custom assets support automated monitoring in dynamic altcoin spaces
- Smoothing and lookbacks balance reactivity with stability for versatile timeframes
- Equal-metric averaging assumes balance , customizable via toggles for bias
ROC Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The ROC Tracker → PROFABIGHI_CAPITAL indicator measures momentum strength by calculating the Rate of Change (ROC) for up to 33 customizable altcoins over a user-specified period, revealing acceleration or deceleration in price movements. It dynamically generates color-gradient tables displaying individual ROC values, median benchmarks, and ranked top momentum performers with emoji indicators, allowing traders to spot surging assets for timely entries or fading ones for exits in volatile markets.
⚙️ General Settings
– ROC Period : Defines the lookback bars for percentage change computation, where shorter periods (e.g., 5-10) highlight immediate momentum bursts while longer spans (e.g., 20-50) capture sustained trends—key for aligning with trading horizons like scalping or swing setups.
💎 Asset Selection Settings
– Number of Altcoins to Display : Scales the primary table from a streamlined 5-asset view for rapid momentum checks to a full 33-symbol scan for broad-market acceleration profiling—balances detail with computational efficiency.
– Number of Top ROC Assets : Configures the momentum leaderboard to emphasize leading changers, adjustable from 1 for focused highlights to the total count for unbridled ranking—accelerates identification of breakout candidates.
– Asset 1-17 (Left Group) : Curates the main table's left column with essential altcoins, enabling personalization from anchors like ETHUSD to varied inclusions such as XRPUSD—each retrieves daily closes for standalone ROC derivation, with tooltips confirming symbol standards.
– Asset 18-33 (Right Group) : Populates the right column for diversified momentum tracking, incorporating further tokens from LTCUSD to specialized selections like MNTUSD—fosters balanced tri-column flow for lateral dataset review.
– Dynamic Input Rendering : Activates fields proportional to asset tally, veiling extras to sidestep errors and simplify navigation—facilitates effortless escalation from narrow lists to panoramic surveillance.
🎨 Table Style Settings
– Low ROC Color : Sets the gradient's deceleration base (e.g., deep red for negative changes), promptly signaling momentum fades that may prompt profit-taking or avoidance.
– High ROC Color : Anchors the acceleration peak (e.g., vivid green for positive changes), illuminating surging movers ripe for momentum continuation plays.
– Neutral ROC Value : Centers the color pivot at zero change (typically 0.0), modulating from loss to gain hues—adjustment biases toward conservative or aggressive momentum reads.
– ROC Color Range : Governs the transitional breadth around neutral, embracing wide fades for nuanced momentum gradients or narrow contrasts for binary surge/lag demarcation.
– Table Background : Deploys a muted dark semi-transparent canvas for thematic unity and cross-theme visibility, crafting an elegant momentum dashboard.
– Table Border : Enframes with neutral gray for subtle containment, encapsulating data without stylistic diversion.
📡 Data Fetching
– Asset Data Retrieval : Conducts concurrent daily close queries for nominated symbols, interposing NA for gaps to fortify table resilience.
– Return Series Computation : Applies 1-period percentage variances to asset paths, yielding the momentum quanta for period-based change metrics.
– Missing Data Resilience : Implants sentinels (-9999) for voids, rendering as grays to indicate incompleteness without structural breach.
🧮 Calculations
– Periodic Return Generation : Computes rate of change over the specified bars as current divided by prior minus unity, distilling momentum as percentage acceleration.
– Raw ROC Derivation : Directly yields the percentage shift over the lookback, quantifying speed without further averaging for pure velocity insight.
– NA Propagation Handling : Forwards missing values to preserve computational chain integrity, displaying as neutrals in outputs.
📋 Table Display
– Dynamic Layout Optimization : Erects columns (up to 9 for tri-set harmony) and rows attuned to asset volume plus header, assuring pithy utility for 1-33 symbols.
– Main Table Architecture : Branded header vaults the apical row, shadowed by asset symbols, rounded momenta (3 decimals), and velocity emojis in parsimonious trios for row-thrifty perusal.
– ROC Color Continuum : Cartographs values from low (red) via neutral (midpoint) to high (green), with grays for voids—precipitates immediate momentum profiling.
– Emoji Velocity Markers : Dispatches rocket for above-median changes (accelerators) and downward arrow for below (decelerators), infusing expeditious visual discernment.
– Median Table Encapsulation : Terse single-column depiction of pivotal momentum with gradient tint, mooring relative appraisals as a parity linchpin.
– Top ROC Table Hierarchy : Descending stratification in 3-column lattice (symbol, value, emoji) with header branding, converging on paramount assets for surge-dominant dispositions.
– Index-Fueled Ranking : Mobilizes array indices for descending distillation, refabricating sorted arrays while custodians originals for scrupulous median genesis.
🔔 Alerts
– Dynamic Alert Fabrication : Erects newline-segmented compendia of symbols and rounded momenta on the ultimate bar, amputating prefixes for laconic phrasing.
– Once-Per-Bar Dispatch : Ignites alerts at closure with the plenary dataset, harmonizing external adjuncts like dispatches or automata.
– Output Refinement : Distills parseable essence by eliding NAs, honing on operable datum for unencumbered conduit amalgamation.
✅ Key Takeaways
– ROC quantification unveils momentum velocity, spotlighting acceleration for timely pursuits.
– Rolling period with direct computation yields crisp, unaltered speed metrics.
– Profuse symbol pliancy forges bespoke crypto velocity observatories from titans to obscurities.
– Gradient lattices with medians and tops hasten surge/lag discernment through optics.
– Automated alerts encapsulate scans into consumable missives, hastening from scrutiny to stratagem.
Omega Ratio Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Omega Ratio Tracker → PROFABIGHI_CAPITAL indicator quantifies the probability-weighted gain-to-loss efficiency by computing the Omega ratio for up to 33 customizable altcoins over a rolling lookback period, contrasting cumulative returns above a user-defined target against those below to assess favorable outcomes. It dynamically constructs color-gradient tables featuring individual Omegas, median benchmarks, and ranked top performers with emoji indicators, allowing traders to evaluate assets' upside potential relative to downside risks for informed, asymmetric opportunity selection.
⚙️ General Settings
– Calculation Period (Bars) : Establishes the historical scope for return accumulation and threshold comparisons, where shorter windows spotlight immediate efficiencies amid market swings while extended periods gauge long-term gain/loss asymmetries—pivotal for matching trading cadences like intraday (e.g., 20-50 bars) or swing (e.g., 100+ bars).
– Target Return per Period (%) : Specifies the aspirational return threshold per bar/day, serving as the pivot separating "gains" from "losses" in the ratio—elevated targets demand superior performance for positive Omegas, ideal for high-conviction filters, while modest ones broaden inclusion for diverse scans.
– Smoothing Period (EMA) : Implements exponential moving average on raw ratios to mitigate transients, with low values (e.g., 1-2) retaining volatility for granular views and higher settings (e.g., 4-7) fostering trend persistence for strategic planning.
💎 Asset Selection Settings
– Number of Altcoins to Display : Dictates the primary table's expanse from a targeted 5-asset spotlight for swift evaluations to a maximal 33-symbol expanse for holistic risk-reward profiling—impacts processing demands and dashboard density.
– Number of Top Omega Assets : Tailors the elite leaderboard to showcase premier ratios, variable from 1 for ultra-focused highlights to the aggregate count for unfiltered excellence—expedites prioritization of high-gain/low-loss candidates.
– Asset 1-17 (Left Group) : Loads the main table's left column with bedrock altcoins, facilitating bespoke curation from stalwarts like ETHUSD to varied mid-tiers such as XRPUSD—each solicits daily closes for autonomous Omega computation, with tooltips validating symbol protocols.
– Asset 18-33 (Right Group) : Charges the right column for augmented diversification, embracing further tokens from LTCUSD to esoteric picks like MNTUSD—cultivates equilibrated tri-column ergonomics for lateral dataset traversal.
– Dynamic Input Activation : Manifests fields per asset tally, obfuscating redundants to forestall faults and declutter—empowers fluid augmentation from succinct rosters to panoramic oversight sans reconfiguration.
🎨 Table Style Settings
– Low Omega Color : Grounds the gradient's unfavorable terminus (e.g., stark red for ratios below 1.0), instantaneously tagging assets with skewed losses over gains that might erode portfolio viability.
– High Omega Color : Secures the advantageous apex (e.g., radiant green for ratios above 1.0), illuminating prospects with dominant upsides relative to downsides for asymmetric edge hunting.
– Neutral Omega Value : Locates the color fulcrum at equilibrium efficiency (typically 1.0 for balanced outcomes), where ratios modulate from penalty to premium—refinement inclines toward prudent or venturesome outlooks.
– Omega Color Range : Regulates the transitional amplitude encircling neutral, favoring expansive fades for refined gradations or constricted shifts for unequivocal high/low bifurcation.
– Table Background : Imposes a discreet dark semi-opaque substrate for thematic cohesion and theme-agnostic legibility, evoking a refined analytics interface.
– Table Border : Encases perimeters with subdued gray for tacit delineation, encapsulating intelligence without stylistic encumbrance.
📡 Data Fetching
– Asset Data Retrieval : Undertakes simultaneous daily close interrogations for nominated symbols, interposing NA for lacunae to buttress table solidity.
– Return Series Computation : Extracts 1-period percentage variances from asset trajectories, proffering the elemental grist for gain/loss partitioning.
– Void Data Fortification : Implants sentinels (-9999) for lacunae, materializing as grays in renderings to signify incompleteness sans architectural compromise.
🧮 Calculations
– Periodic Return Generation : Forges bar/daily percentage alterations as source divided by antecedent minus unity, underpinning the discrete quanta for target-relative dissection.
– Target Threshold Decimalization : Transmutes percentage input to fractional form, delineating the demarcation betwixt accretive and detractive outcomes.
– Cumulative Gain Accrual : Aggregates excesses above target over the period, encapsulating favorable deviations' aggregate potency.
– Cumulative Loss Accrual : Tallies shortfalls below target, quantifying adverse deviations' collective burden.
– Raw Omega Formulation : Divides gains by losses, yielding the probability-adjusted efficiency quotient—defaults to NA on nil losses for interpretive clarity.
– EMA Transient Suppression : Exponentially averages raw quotients to quell ephemera, engendering interpretable contours over jagged dailies.
– Annualization Omission : Presents periodic ratios without scaling, prioritizing raw bar-level insights for intraday or short-term applicability.
📋 Table Display
– Dynamic Layout Optimization : Assembles columns (apex 9 for tri-set orchestration) and rows calibrated to asset quantum plus header, vouchsafing succinct potency for 1-33 symbols.
– Main Table Architecture : Branded header vaults the apical row, shadowed by asset symbols, rounded quotients (3 decimals), and efficiency emojis in parsimonious trios for row-thrifty perusal.
– Omega Color Continuum : Cartographs values from low (red) via neutral (midpoint) to high (green), with grays for voids—precipitates immediate gain/loss equilibrium profiling.
– Emoji Efficiency Markers : Dispatches rocket for above-median quotients (asymmetric victors) and downward arrow for below (lopsided laggards), infusing expeditious visual discernment.
– Median Table Encapsulation : Terse single-column depiction of pivotal quotient with gradient tint, mooring relative appraisals as a parity linchpin.
– Top Omega Table Hierarchy : Descending stratification in 3-column lattice (symbol, value, emoji) with header branding, converging on paramount assets for gain-dominant dispositions.
– Index-Fueled Ranking : Mobilizes array indices for descending distillation, refabricating sorted arrays while custodians originals for scrupulous median genesis.
🔔 Alerts
– Dynamic Alert Fabrication : Erects newline-segmented compendia of symbols and rounded quotients on the ultimate bar, amputating prefixes for laconic phrasing.
– Once-Per-Bar Dispatch : Ignites alerts at closure with the plenary dataset, harmonizing external adjuncts like dispatches or automata.
– Output Refinement : Distills parseable essence by eliding NAs, honing on operable datum for unencumbered conduit amalgamation.
✅ Key Takeaways
– Gain/loss partitioning via target thresholds unveils asymmetric efficiency beyond traditional metrics.
– Rolling computations with smoothing furnish trend-stable, noise-attenuated efficiency vistas.
– Profuse symbol pliancy forges bespoke crypto observatories from titans to obscurities.
– Gradient lattices with medians and tops hasten low-loss/high-gain discernment through optics.
– Automated alerts encapsulate scans into consumable missives, hastening from scrutiny to stratagem.
Sortino Ratio Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Sortino Ratio Tracker → PROFABIGHI_CAPITAL indicator assesses downside risk-adjusted performance by computing the Sortino ratio for up to 33 customizable altcoins over a rolling lookback period, focusing solely on negative volatility to penalize harmful deviations while smoothing and annualizing for actionable insights. It dynamically generates color-gradient tables displaying individual Sortinos, median benchmarks, and ranked top performers with emoji indicators, empowering traders to prioritize assets with superior returns relative to their drawdown risks for more resilient portfolio construction.
⚙️ General Settings
– Calculation Period (Days/Bars) : Specifies the historical window for return averaging and downside deviation estimation, where shorter periods emphasize recent efficiency amid volatility spikes while longer horizons evaluate enduring downside protection—vital for aligning with strategies like short-term trading (e.g., 30-60 bars) versus long-term holding (e.g., 90+ bars).
– Annual Risk-Free Rate (%) : Sets the threshold below which returns are considered "downside," typically a conservative benchmark like treasury yields—higher rates raise the bar for positive Sortinos, favoring only truly superior risk-adjusted outcomes.
– Smoothing Period (EMA) : Applies exponential moving average to raw ratios for noise reduction, where minimal smoothing (e.g., 1-3) preserves granularity for active monitoring while higher values (e.g., 5+) yield trend-stable views for strategic overviews.
– Number of Altcoins to Display : Determines the primary table's breadth from a streamlined 5-asset focus for rapid scans to a thorough 33-symbol panorama for exhaustive downside risk profiling—directly affects data processing and visual footprint.
– Number of Top Sortino Assets : Configures the leaderboard to spotlight leading ratios, scalable from 1 for laser-focused highlights to the full asset set for complete efficiency hierarchy—facilitates prioritization of low-downside winners.
💎 Asset Selection Settings
– Asset 1-17 (Left Group) : Fills the main table's left column with cornerstone altcoins, enabling tailored selection from majors like ETHUSD to diversified options such as XRPUSD—each pulls daily closes for standalone Sortino computation, with tooltips verifying symbol conventions.
– Asset 18-33 (Right Group) : Loads the right column for extended diversification, incorporating further tokens from LTCUSD to specialized choices like MNTUSD—promotes balanced tri-column ergonomics for fluid cross-dataset comparison.
– Dynamic Input Activation : Renders fields conditionally on total assets, hiding extras to avert errors and declutter the interface—supports frictionless growth from compact portfolios to all-encompassing surveillance.
🎨 Table Style Settings
– Low Sortino Color : Establishes the gradient's downside anchor (e.g., intense red for negative ratios), immediately flagging assets with excessive harmful volatility that could undermine portfolio stability.
– High Sortino Color : Pins the excellence terminus (e.g., luminous green for positive ratios), illuminating low-risk/high-return standouts perfect for conservative growth strategies.
– Neutral Sortino Value : Positions the color inflection at breakeven efficiency (typically 0.0), pivoting hues from penalty to premium—tweaking recalibrates toward defensive or opportunistic lenses.
– Sortino Color Range : Modulates the spectrum's transitional span around neutral, opting for broad fades in subtle differentiation or tight contrasts for stark performer/laggard splits.
– Table Background : Instills a understated dark semi-transparent foundation for unified readability across themes, evoking a sleek, professional analytics dashboard.
– Table Border : Circumscribes frames with unobtrusive gray for gentle containment, directing focus to the gradient-infused data without stylistic interference.
📡 Data Fetching
– Asset Data Retrieval : Performs concurrent daily close queries for specified symbols, substituting NA for voids to sustain table robustness.
– Return Series Computation : Extracts 1-period percentage changes from asset series, supplying the granular inputs for mean and downside deviation metrics.
– Missing Data Resilience : Employs sentinels (-9999) for gaps, manifesting as grays in tables to denote incompleteness without layout disruption.
🧮 Calculations
– Periodic Return Generation : Derives daily/bar percentage changes as source over prior close minus one, capturing discrete movements for efficiency evaluation.
– Mean Return Estimation : Averages returns over the rolling period with simple moving average, forging a baseline excess performance metric.
– Downside Deviation Quantification : Sums squared deviations below the risk-free threshold, averaging to measure only harmful volatility—ignores upside for focused risk penalization.
– Raw Sortino Formulation : Divides mean excess return by downside deviation, defaulting to zero on nil volatility for computational safety.
– EMA Noise Attenuation : Exponentially smooths raw ratios to filter transients, yielding interpretable trends over erratic daily swings.
– Annualization Adjustment : Scales smoothed ratios by the square root of 365 (crypto calendar), transforming periodic efficiency into yearly benchmarks for cross-asset comparability.
📋 Table Display
– Dynamic Layout Scaling : Erects columns (maximum 9 for tri-set grouping) and rows attuned to asset quantity plus header, guaranteeing compact utility for 1-33 symbols.
– Main Table Architecture : Branded header traverses the summit row, pursued by asset symbols, rounded ratios (3 decimals), and efficiency emojis in efficient trios for streamlined row navigation.
– Sortino Color Continuum : Maps values from low (red) via neutral (midpoint) to high (green), with grays for voids—enables instantaneous downside efficiency profiling.
– Emoji Efficiency Markers : Deploys rocket for above-median ratios (superior performers) and downward arrow for below (inferior), infusing swift visual assessment.
– Median Table Encapsulation : Succinct single-column portrayal of central ratio with gradient hue, anchoring relative evaluations as a risk-neutral pivot.
– Top Sortino Table Hierarchy : Descending classification in 3-column matrix (symbol, value, emoji) with header branding, concentrating on elite assets for downside-focused decisions.
– Index-Fueled Ranking : Exploits array indices for descending extraction, reconstructing sorted arrays while preserving originals for exact median derivation.
🔔 Alerts
– Dynamic Alert Fabrication : Constructs newline-separated assemblages of symbols and rounded ratios on the terminal bar, excising prefixes for terse formatting.
– Once-Per-Bar Dispatch : Initiates alerts at close with the complete dataset, accommodating external integrations like notifications or automated systems.
– Output Refinement : Curates parseable content by excluding NAs, zeroing in on executable data for streamlined workflow incorporation.
✅ Key Takeaways
– Downside-focused Sortino ratios spotlight assets excelling in returns per harmful volatility unit.
– Rolling computations with smoothing and annualization yield comparable, trend-stable efficiency metrics.
– Vast symbol adaptability crafts bespoke crypto dashboards from majors to alts.
– Gradient tables with medians and tops accelerate low-risk winner identification via visuals.
– Automated alerts consolidate scans into digestible packets, expediting from evaluation to execution.
Sharpe Ratio Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Sharpe Ratio Tracker → PROFABIGHI_CAPITAL indicator evaluates risk-adjusted performance by computing the Sharpe ratio for up to 33 customizable altcoins over a rolling lookback period, smoothing values for stability and annualizing for comparability. It dynamically renders color-gradient tables showcasing individual Sharpe ratios, median benchmarks, and ranked top performers with emoji indicators, enabling traders to identify assets delivering superior returns per unit of volatility for optimized portfolio selection.
⚙️ General Settings
– Sharpe Rolling Period : Adjustable lookback window for return and volatility averaging, where shorter horizons capture recent efficiency while longer spans assess sustained performance stability.
– Smoothing Period : EMA length applied to raw ratios to dampen noise, promoting smoother trends for clearer visual and analytical insights.
– Number of Altcoins to Display : Scales the primary table's capacity from a focused 5-asset scan for quick reviews to a full 33-symbol matrix for comprehensive risk-adjusted screening.
– Number of Top Sharpe Assets : Curates the leaderboard to emphasize leading ratios, tunable from 1 for pinpoint focus to the total count for exhaustive ranking of efficiency standouts.
💎 Asset Selection Settings
– Asset 1-17 (Left Group) : Populates the main table's left column with foundational altcoins, supporting customization from blue-chips like ETHUSD to diversified selections such as XRPUSD—each input retrieves daily closes for isolated Sharpe derivation, with tooltips ensuring accurate symbol formatting.
– Asset 18-33 (Right Group) : Fills the right column for broader exposure, accommodating additional tokens from LTCUSD to niche assets like MNTUSD—facilitates ergonomic tri-column layout for horizontal scanning across the expanded dataset.
– Dynamic Input Rendering : Conditionally activates fields based on total assets, concealing unused slots to eliminate errors and streamline the interface—allows effortless scaling from compact watchlists to exhaustive monitoring without reconfiguration.
🎨 Table Style Settings
– Low Sharpe Color : Anchors the gradient's underperformance base (e.g., deep red for negative ratios), visually flagging assets with poor efficiency that may drag portfolio returns.
– High Sharpe Color : Establishes the excellence endpoint (e.g., vivid green for positive ratios), spotlighting high-efficiency performers ideal for risk-conscious allocations.
– Neutral Sharpe Value : Centers the color pivot at breakeven efficiency (typically 0.0), where ratios shift from subdued to vibrant hues—calibration tilts toward conservative or aggressive interpretations.
– Sharpe Color Range : Broadens or narrows the transition zone around neutral, yielding gradual blends for nuanced rankings or sharp delineations for clear high/low separation.
– Table Background : Deploys a subtle dark semi-transparent canvas for all views, fostering glare-free readability across themes while delivering a cohesive dashboard appearance.
– Table Border : Frames outlines with neutral gray for understated structure, containing content without diverting from the gradient-centric data narrative.
📡 Data Fetching
– Asset Data Retrieval : Executes parallel daily close requests for designated symbols, gracefully managing empty inputs by inserting NA placeholders to uphold table cohesion.
– Return Series Computation : Derives 1-period percentage changes for each asset, furnishing the discrete inputs for mean and standard deviation estimations.
– Invalid Data Mitigation : Substitutes missing values with sentinels (-9999) for rendering as grays, preserving layout amid incomplete datasets.
🧮 Calculations
– Daily Return Generation : Applies rate of change over one day to each asset's series, yielding percentage shifts as the core for efficiency metrics.
– Mean Return Smoothing : Averages returns over the rolling period via simple moving average, establishing historical performance baselines.
– Standard Deviation Volatility : Computes rolling dispersion of returns, quantifying risk as the denominator for ratio normalization.
– Raw Sharpe Derivation : Divides mean return by standard deviation, handling zero-volatility cases with zero fallback for stability.
– EMA Smoothing Application : Applies exponential moving average to raw ratios, attenuating fluctuations for trend-revealing outputs.
– Annualization Scaling : Multiplies smoothed ratios by the square root of 365, converting daily efficiency to yearly comparability.
📋 Table Display
– Dynamic Layout Optimization : Constructs columns (up to 9 for tri-set configuration) and rows scaled to asset count plus header, ensuring compact efficiency for 1-33 symbols.
– Main Table Framework : Branded header bridges the top row, trailed by asset symbols, rounded ratios (3 decimals), and efficiency emojis in streamlined trios for row-efficient navigation.
– Sharpe Color Continuum : Interpolates from low (red) through neutral (midpoint) to high (green), with grays for invalids—facilitates at-a-glance risk-adjusted profiling.
– Emoji Efficiency Markers : Renders rocket for above-median ratios (strong performers) and downward arrow for below (weak), injecting rapid visual sentiment.
– Median Table Encapsulation : Compact single-column showcase of central ratio with gradient coloring, anchoring relative evaluations as an efficiency fulcrum.
– Top Sharpe Table Hierarchy : Descending rank in 3-column array (symbol, value, emoji) with header branding, zeroing in on superior assets for allocation prioritization.
– Index-Fueled Ranking : Harnesses array indices for descending extraction, rebuilding sorted arrays while safeguarding originals for precise median derivation.
🔔 Alerts
– Dynamic Alert Fabrication : Assembles newline-separated compilations of symbols and rounded ratios on the final bar, purging prefixes for succinct formatting.
– Once-Per-Bar Dispatch : Activates alerts at close with the full dataset, accommodating external integrations like notifications or bots.
– Output Refinement : Curates parseable content by excluding NAs, concentrating on executable data for seamless workflow embedding.
✅ Key Takeaways
– Transforms risk-adjusted efficiency into gradient-scored tables for effortless asset ranking.
– Rolling Sharpe with smoothing and annualization delivers comparable, noise-reduced insights.
– Extensive symbol flexibility supports tailored crypto portfolios from majors to alts.
– Top medians and emojis accelerate outperformance detection with visual punch.
– Automated alerts package complete scans, streamlining from analysis to action.
