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Stocks: Dashboard [invincible3]Stocks Dashboard is a professional all-in-one stock analysis dashboard built directly for TradingView charts. It is designed to help investors, traders, and analysts quickly evaluate a stock using a combination of fundamental strength, valuation, financial health, income quality, shareholder return, and price momentum.
The indicator displays a clean table-based dashboard on the chart and converts raw financial and technical data into easy-to-read category scores. Instead of checking many separate financial ratios manually, this dashboard organizes the most important stock metrics into structured sections and gives a clear visual overview of the company’s current condition.
The dashboard includes composite scoring for Quality, Value, Growth, Financial Health, Income / Shareholder Return, and Momentum. Each category is scored from 0 to 100 and classified using simple rating labels such as Elite, Strong, Fair, Weak, or Risk. This allows users to quickly compare the strength and weakness of a stock across multiple dimensions.
The Valuation section includes important valuation metrics such as P/E TTM, Forward P/E, PEG Ratio, P/S, P/B, EV/EBITDA, EV/Sales, Earnings Yield, Operating Earnings Yield, Graham Price, Graham Number Upside, EPS TTM, and BVPS. These metrics help identify whether a stock may be expensive, fairly valued, or potentially undervalued.
The Quality section focuses on profitability and business efficiency. It includes ROE, Asset Return / ROA, ROIC, Piotroski F-Score, Gross Margin, Operating Margin, Net Margin, EBITDA Margin, and Free Cash Flow Margin. These values help evaluate how efficiently the company generates profits from its assets, equity, capital, revenue, and operations.
The Growth section tracks the company’s expansion profile using Revenue Growth, EPS Growth, and Sustainable Growth Rate. These metrics help users understand whether the business is improving, stagnating, or losing earnings momentum.
The Financial Health section evaluates balance sheet strength and risk. It includes Debt / Equity, Debt / Assets, Debt / EBITDA, Net Debt / EBITDA, Cash / Debt, Current Ratio, Quick Ratio, Interest Coverage, Altman Z-Score, Operating Cash Flow, and Free Cash Flow. This section is useful for identifying companies with strong liquidity, manageable debt, and lower financial risk.
The Income / Return section is designed for dividend and shareholder-return analysis. It includes Dividend Yield, Payout Ratio, Free Cash Flow Yield, DPS, Buyback Yield, and Buyback Ratio. These metrics help investors evaluate whether a company is returning value to shareholders through dividends, buybacks, and cash generation.
The Momentum section adds a technical view of the stock. It includes RSI 14, 1-month return, 3-month return, 6-month return, 12-month return, 6-month relative strength versus a selected benchmark, 12-month relative strength versus a selected benchmark, volatility, and moving-average trend using the 20, 50, and 200 daily moving averages.
The Snapshot section provides a quick summary of the selected stock, including current price, market capitalization, enterprise value, 52-week position, and distance from the 52-week high. This gives users a fast overview of where the stock is trading relative to its recent range.
Users can customize the stock symbol, benchmark/index symbol, financial period, table position, text size, color theme, and visible sections. The dashboard supports multiple professional themes, including Dark Terminal, Light Terminal, Emerald Pro, Royal Blue, and Amber Desk. Users can also enable or disable colored score backgrounds, score bars, alternating rows, colorful section headers, and directional symbols.
This indicator is useful for:
* Long-term stock analysis
* Fundamental screening
* Valuation comparison
* Dividend and shareholder-return review
* Financial health analysis
* Momentum confirmation
* Relative strength comparison against an index or benchmark
* Building a structured watchlist review process
The goal of this dashboard is to provide a fast, organized, and visually professional stock overview without requiring users to switch between multiple financial websites or separate indicators. It combines fundamental data and technical momentum into one compact chart-based table, making it easier to identify strong, weak, undervalued, overvalued, or financially risky stocks.
Note: The dashboard uses TradingView’s available financial data. Some metrics may appear unavailable depending on the selected symbol, exchange, market, or financial data coverage. This tool is intended for analysis and research purposes only and should not be considered financial advice.
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Stock: Comparison Dashboard [invincible3]Stock: Comparison Dashboard
**Stock: Comparison Dashboard ** is a fundamental and market-strength comparison tool designed to compare two stocks side by side directly on the TradingView chart.
The dashboard helps traders and investors quickly evaluate which stock is stronger across multiple financial dimensions, including growth, income statement strength, profitability, valuation, cash flow quality, financial strength, liquidity, dividend quality, and relative price strength.
Key Features
1. Two-Stock Comparison
Select any two symbols and compare their financial metrics side by side. The dashboard displays both raw values and category-based scores.
2. Fundamental Metrics
The indicator includes a wide set of financial metrics, such as:
* Revenue growth
* EPS growth
* Total revenue
* Operating income
* Net income
* Margins
* Return on equity
* Price-to-earnings ratio
* Price-to-sales ratio
* Free cash flow
* Debt ratios
* Current ratio
* Dividend yield
* Dividend payout ratio
3. Category Scores
The dashboard calculates separate comparison scores for:
* Growth Score
* Income Score
* Profitability Score
* Valuation Score
* Cash Flow Score
* Financial Strength Score
* Liquidity Score
* Dividend Score
* Relative Strength Score
4. Proportional Scoring System
The scoring system uses proportional comparison instead of simple winner-take-all logic.
For example, if one stock has 16% growth and another has 18% growth, the weaker stock does not receive 0. Instead, both stocks receive proportional scores based on how close their values are.
This makes the dashboard more realistic and useful for financial analysis.
5. Relative Strength Score
The Relative Strength Score compares the market performance of both stocks using:
* 3-month price performance
* 6-month price performance
* 12-month price performance
* Position within the 52-week range
* Distance from the 200-day moving average
This helps identify which stock has stronger market momentum.
6. Better / Weaker Value Highlighting
Better and weaker values are highlighted using text color instead of heavy background coloring. This keeps the table cleaner and easier to read.
7. Light and Dark Table Themes
The dashboard includes both light and dark table themes, making it suitable for different TradingView chart layouts.
8. Customizable Rows
Each category allows the user to choose which metrics to display. Unwanted rows can be set to “None” to keep the dashboard clean.
How to Use
1. Select Stock 1 and Stock 2 from the indicator settings.
2. Choose the financial period: Quarter or Year.
3. Select the metrics you want to compare in each category.
4. Choose Light or Dark table theme.
5. Read the raw values and comparison scores to identify the stronger stock.
Interpretation
A higher score means the stock is stronger in that specific category.
Example:
* Higher Growth Score = stronger growth profile
* Higher Profitability Score = better profitability
* Higher Valuation Score = more attractive valuation
* Higher Financial Strength Score = stronger balance sheet
* Higher Relative Strength Score = stronger market momentum
Important Notes
This indicator uses TradingView financial data. Some financial fields may be unavailable for certain stocks, exchanges, or periods. If a metric is unavailable, the table may show a dash.
TradingView also has request limits, so the dashboard is designed to keep the number of active financial rows under control.
This indicator is intended for research, comparison, and educational analysis only. It is not financial advice. Always combine fundamental analysis with your own research, risk management, and market context.
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Stock: Snowflake Analysis [invincible3]Stock: Snowflake Analysis
Stock: Snowflake Analysis is a visual fundamental-analysis radar indicator designed for stock traders and investors who want a quick, structured view of a company’s financial quality. The indicator converts multiple TradingView financial metrics into normalized 0–100 scores and displays them as a six-axis snowflake/radar chart directly on the price chart.
The purpose of the indicator is to help users quickly evaluate a stock from several key perspectives: dividend quality, growth, inventory efficiency, financial stability, valuation, and future outlook. Each metric is transformed into a score, then plotted visually so the user can immediately see where a company is strong or weak. The current script uses six core categories: Dividend, Growth, Inventory, Stability, Valuation, and Future, and it draws the final score as a radar/snowflake polygon.
Main Concept
The indicator works by pulling available stock financial data from TradingView using request.financial(). These values are then normalized into scores from 0 to 100.
A score near 100 means the company is strong in that category.
A score near 50 means the company is neutral or average.
A score near 0 means the company is weak in that category.
The final snowflake shape gives a quick visual overview:
A large, balanced snowflake suggests broad financial strength.
A small or uneven snowflake suggests weakness or imbalance.
A stretched shape shows that the company is strong in some areas but weak in others.
Six Core Financial Categories
1. Dividend Score
The Dividend axis evaluates whether the stock provides attractive and sustainable shareholder distributions.
It uses:
Dividend yield
Dividend payout ratio
The dividend yield is scored positively when it is higher, while the payout ratio is scored negatively if it becomes too high. A very high payout ratio may suggest that the dividend is less sustainable.
A strong Dividend score usually means the company has a decent yield without excessive payout pressure.
2. Growth Score
The Growth axis measures how well the company is expanding.
It uses:
Revenue growth
EPS growth
Gross margin
The score rewards companies with improving sales, stronger earnings, and healthier gross margins. A company with strong revenue growth but weak margins may receive a mixed score, while a company with both growth and profitability receives a stronger score.
This category is especially useful for identifying companies with improving business momentum.
3. Inventory Score
The Inventory axis evaluates operating efficiency, especially for businesses where inventory management matters.
It uses:
Inventory turnover
Inventory-to-revenue ratio
Higher inventory turnover is considered positive because it suggests that the company sells its inventory efficiently. A lower inventory-to-revenue ratio is also considered positive because it indicates that inventory is not becoming too heavy relative to sales.
This score is more useful for retail, manufacturing, consumer goods, and industrial companies. It is less meaningful for banks, software companies, or service businesses.
4. Stability Score
The Stability axis measures balance-sheet strength.
It uses:
Current ratio
Debt-to-equity ratio
A higher current ratio generally suggests better short-term liquidity, while a lower debt-to-equity ratio suggests lower financial leverage.
A strong Stability score means the company appears financially safer and less dependent on debt. A weak score may suggest liquidity pressure or excessive leverage.
5. Valuation Score
The Valuation axis evaluates whether the stock appears reasonably priced relative to earnings.
It uses:
Earnings yield
Price-to-earnings ratio
Earnings yield is calculated as:
Earnings Yield = EPS / Price × 100
A higher earnings yield is better. A lower P/E ratio is also better, up to a reasonable threshold. This category rewards companies that generate meaningful earnings relative to their current share price.
A high Valuation score may suggest the stock is cheaper relative to earnings, while a low score may suggest the stock is expensive or earnings are weak.
6. Future Score
The Future axis attempts to measure forward-looking quality.
It uses:
Sustainable growth rate
Forward P/E ratio
A higher sustainable growth rate improves the score, while a very high forward P/E lowers the score. This category tries to balance future growth potential with future valuation risk.
A strong Future score suggests the stock may have a reasonable combination of expected growth and forward valuation.
Final Score
The center score is calculated as the average of the six category scores:
Final Score = Average of Dividend, Growth, Inventory, Stability, Valuation, and Future
This final score is displayed in the center of the radar chart.
The score color changes dynamically using the indicator’s heatmap color theme:
Low scores appear in purple tones.
Mid scores appear in teal tones.
High scores appear in green/yellow tones.
This makes it easier to visually identify weak, neutral, and strong readings.
Visual Design
The indicator displays a clean snowflake/radar chart directly on the price chart. Each axis represents one financial category.
Visual components include:
Hexagonal grid rings
Axis lines
Category labels
Score markers
Filled snowflake polygon
Dynamic color based on total score
Optional historical comparison snowflake
The snowflake is placed to the right side of the latest bar using the Right Offset setting, so it does not cover the current candles.
Historical Comparison
The indicator includes an optional Historical Snowflake feature.
When enabled, it compares the current snowflake with a previous score profile based on the selected historical lookback.
For example:
Historical Lookback = 252 bars
This can be used as an approximate one-year comparison on daily charts.
The historical snowflake helps users see whether the company’s fundamental profile has improved, weakened, or remained stable over time.
Stock-Only Protection
This indicator is designed for stock symbols only because financial metrics such as dividend yield, payout ratio, EPS, revenue growth, and debt-to-equity are stock/company-specific data.
For non-stock symbols such as:
Gold
Forex pairs
Crypto
Indices
Commodities
the script does not draw the snowflake. Instead, it displays a warning message explaining that financial metrics are not available for those instruments.
This prevents misleading neutral scores from appearing on symbols where company financial data does not exist.
Input Settings
Radar Layout
Right Offset Bars
Moves the snowflake to the right side of the latest candle.
Scale Lookback
Controls the price range used to vertically scale the snowflake on the chart. This does not affect the financial scores.
Width
Controls the horizontal size of the radar.
Height %
Controls the vertical size of the radar relative to the recent price range.
Label Distance
Controls how far the category labels are placed from the radar center.
Visual Styling
Show Grid Rings
Turns the hexagonal background rings on or off.
Show Axis Lines
Turns the center-to-axis guide lines on or off.
Show Axis Labels
Shows or hides the category names and scores.
Show Score Markers
Shows or hides circular markers at each snowflake point.
Dynamic Colors
When enabled, the snowflake color changes based on the total average score.
Marker Size
Controls the size of the score markers.
Historical Comparison
Show Historical Snowflake
Displays a previous score profile for comparison.
Historical Lookback Bars
Defines how far back the comparison should be calculated.
How to Interpret the Snowflake
A strong stock usually shows:
A broad and balanced snowflake
High Growth and Stability scores
Reasonable Valuation score
Improving Future score
A risky or weak stock may show:
A compressed snowflake
Very low Stability
Weak Growth
Expensive Valuation
Poor Future score
An unbalanced company may show a stretched snowflake. For example, a high Growth score but low Stability and Valuation scores may indicate a fast-growing but financially risky or expensive company.
Best Use Cases
This indicator is useful for:
Quick stock screening
Comparing companies visually
Identifying financial strengths and weaknesses
Monitoring changes in a company’s financial profile
Combining fundamentals with technical analysis
Long-term investing and swing-trading research
It is especially helpful when comparing stocks within the same sector.
Important Notes
The indicator uses a generic scoring model. Different sectors naturally have different financial structures.
For example:
Banks do not use inventory metrics in the same way as retail companies.
Utilities often carry higher debt.
Technology companies may have low dividend scores but strong growth.
Retail and manufacturing companies rely more heavily on inventory efficiency.
Because of this, the scores should be interpreted with sector context.
Limitations
This indicator should not be used as a standalone buy or sell signal.
Financial data can be delayed, unavailable, or inconsistent depending on the symbol and exchange. When a financial metric is missing, the script uses a neutral internal fallback value to keep the radar visually stable.
The indicator is best used as a summary and comparison tool, not as a complete valuation model.
Disclaimer
Snowflake Analysis is an educational and research tool. It is not financial advice. Users should always combine this indicator with their own analysis, sector research, risk management, and broader market context before making trading or investment decisions. مؤشر
AI UltraTrend X Pro V1The AI UltraTrend X Pro V1 is a high-performance, signal-based indicator engineered to identify explosive trend reversals while aggressively filtering out sideways market noise. Built specifically to handle high-volatility environments like BankNifty, this tool excels at capturing large point moves by combining institutional flow tracking with advanced price-action breakouts.
Key Features
Multi-Segment Mastery: While optimized for the fast-paced nature of BankNifty, the logic is universally applicable across Equity, Forex, Commodities, and Crypto.
Optimized for 3m+ Timeframes: Designed for the 3-minute duration and above, providing a perfect balance between early entries and noise reduction.
Hybrid Execution Logic: Unlike standard indicators that rely solely on crossovers, this script uses a dual-trigger system—line crosses and volatility-backed breakouts—ensuring you never miss a gap-up or a sudden trend explosion.
Intraday & Swing Flexibility: Seamlessly transitions between aggressive Intraday scalping and Positional trend following. The indicator maintains its state, allowing users to carry trades or square off at the end of the session based on their own risk profile.
Advanced Anti-Chop Shield: Features a built-in Volume & Volatility filter that identifies "dead zones" (gray signal areas) to prevent the "multiple entries/exits" common in flat markets.
Dynamic Trailing Stop-Loss: Plots a real-time, ATR-based trailing exit (Yellow Line) that locks in profits while giving the trend enough "breathing room" to survive minor pullbacks.
How to Use
Enter CE: Triggered when the signal turns Green and price breaks recent resistance.
Enter PE: Triggered when the signal turns Red and price breaks recent support.
Stay with the Trend: The background remains color-coded (Green/Red) as long as the trend is healthy.
Exit: Close your position when the signal label flips.
Best Settings
Timeframe: 3m, 5m, or 15m.
Chart: Works best on standard Candlesticks or Heikin Ashi for smoother trend following. مؤشر
BTC Valuation Cycle [Alpha Extract]A sophisticated multi-metric Bitcoin valuation framework that synthesizes on-chain analytics including SOPR, MVRV, Price-to-Realized, and Mayer Multiple into a unified 0-100 cycle oscillator with six-tier zone classification for market cycle identification. Utilizing logistic transformation with configurable weighting and z-score normalization, this indicator delivers institutional-grade Bitcoin-specific valuation assessment with pivot-based extreme detection and comprehensive alert system. The system's weighted composite architecture combined with adaptive curve intensity enables precise calibration of cycle sensitivity while maintaining statistical validity across Bitcoin's multi-year market cycles.
🔶 Advanced Multi-Metric Synthesis Engine
Implements sophisticated composite calculation combining four distinct Bitcoin valuation metrics with configurable weighting and normalization framework. The system retrieves SOPR (Spent Output Profit Ratio), MVRV (Market Value to Realized Value), Price-to-Realized ratio, and Mayer Multiple from on-chain sources, applies z-score normalization to each metric over configurable periods, transforms via logistic function for 0-100 scaling, and generates weighted average creating unified cycle score.
// Component Score Calculation
SOPR_Centered = SOPR - 1.0
SOPR_Z = z_score(SOPR_Centered, Normalization_Length)
SOPR_Score = logistic_100(SOPR_Z, Curve_Intensity)
Price_to_Realized_Z = z_score(Price / Realized_Price, Normalization_Length)
PR_Score = logistic_100(Price_to_Realized_Z, Curve_Intensity)
MVRV_Z = z_score(Market_Cap / Realized_Cap, Normalization_Length)
MVRV_Score = logistic_100(MVRV_Z, Curve_Intensity)
Mayer_Z = z_score(Mayer_Multiple, Normalization_Length)
Mayer_Score = logistic_100(Mayer_Z, Curve_Intensity)
// Weighted Composite
Cycle = (SOPR_Score × W_SOPR + PR_Score × W_PR + MVRV_Score × W_MVRV + Mayer_Score × W_Mayer) / (W_SOPR + W_PR + W_MVRV + W_Mayer)
🔶 Understanding Bitcoin Valuation Metrics
SOPR (Spent Output Profit Ratio) measures the degree of profit for coins moved on-chain, calculated as value sold divided by value paid. Values above 1.0 indicate profitable selling (distribution), below 1.0 indicate loss-taking (capitulation). The system centers SOPR around 1.0 for normalization.
MVRV (Market Value to Realized Value) compares current market cap to realized cap (aggregate cost basis). High MVRV signals overvaluation as price exceeds average acquisition cost; low
MVRV suggests undervaluation. The system offers Ratio mode (raw MVRV), Z-Score mode (statistical deviation), or Blend mode (average of both).
Price-to-Realized Ratio directly compares current BTC price to realized price (realized cap divided by circulating supply), providing cleaner valuation signal than MVRV by removing market cap distortions.
Mayer Multiple measures price relative to 200-day moving average. Values above 2.4 historically mark tops; values near or below 1.0 mark bottoms. The system normalizes this classic technical indicator alongside on-chain metrics.
🔶 Logistic Transformation Framework
Features sophisticated logistic function application converting unbounded z-scores into bounded 0-100 range with configurable curve intensity controlling sensitivity. The system applies formula: 100 / (1 + exp(-z × k)) where z is z-score and k is curve intensity (default 0.90), creates S-curve transformation preserving relative relationships while preventing extreme outliers, and enables smooth gradient visualization across entire cycle range.
🔶 Six-Tier Cycle Zone Classification
Implements comprehensive market cycle framework dividing 0-100 range into six distinct zones with configurable thresholds representing Bitcoin's characteristic bubble and bust patterns. The system defines Bottom Extreme (default <10, accumulation zone), Cold Zone (10-25, early recovery), Lower Mid (25-40, neutral to bullish), Upper Mid (40-60, bullish), Hot Zone (60-75, late bull market), and Top Extreme (>75, euphoria/distribution) with dynamic color coding.
🔶 Pivot-Based Extreme Detection System
Provides intelligent local extreme identification using pivot high/low detection with zone threshold filtering and visual capsule markers. The system detects pivot highs above Hot Zone threshold and pivot lows below Cold Zone threshold using configurable left/right bars, creates horizontal capsule visualizations at exact extreme values with color-coded centers (red for tops, cyan for bottoms), and maintains rolling array limited to maximum capsule count for clean chart presentation.
🔶 MVRV Calculation Mode Selection
Offers three distinct MVRV calculation approaches optimizing for different market conditions and analytical preferences. Ratio mode uses raw Market Cap / Realized Cap for direct valuation comparison, Z-Score mode applies statistical normalization emphasizing deviations from historical mean, and Blend mode (default) averages both approaches balancing absolute valuation with statistical context for robust signal generation.
🔶 Configurable Metric Weighting System
Features flexible weight allocation enabling traders to emphasize preferred metrics or disable unreliable components during specific market regimes. The system accepts 0.0-N weight values for each metric (default 1.0 all equal), automatically handles missing data by excluding NA metrics from composite, recalculates weighted average dynamically, and enables custom cycle calibration based on trader's confidence in different on-chain signals.
🔶 Confirmed HTF Data Integration
Implements rigorous anti-repaint methodology using confirmed higher-timeframe values with offset preventing live bar distortion. The system retrieves all on-chain metrics from daily timeframe with 1-bar offset ensuring only completed daily candle data influences cycle score, applies identical offset to Mayer Multiple calculation, and maintains signal stability across real-time updates preventing false extreme alerts.
🔶 Comprehensive Alert Framework
Provides five distinct alert conditions covering critical cycle events and threshold breaches with descriptive messages. The system triggers Top Extreme alert on crossover above top threshold (default 90), Bottom Extreme alert on crossunder below bottom threshold (default 10), Hot Rejection alert when cycle falls from Hot Zone, Cold Reclaim alert when cycle rises from Cold Zone, and Mayer Threshold breach alert for traditional technical confirmation.
🔶 Gradient Zone Visualization Architecture
Creates intuitive color-coded area plot with six distinct color zones reflecting current cycle position through visual spectrum from cyan (extreme bottom) through purple/orange to red (extreme top). The system applies dynamic zone coloring to both area fill and cycle value display, implements configurable area transparency (default opaque), and maintains consistent color scheme across oscillator pane, table values, and capsule markers.
🔶 Real-Time Diagnostics System
Features comprehensive data availability monitoring with missing metric labels and detailed value table showing all component metrics. The system detects NA values in SOPR, Realized Price, MVRV, or Mayer Multiple, displays warning label listing unavailable metrics, and provides table overlay showing current values for Cycle score, all four components, MVRV-Z, Mayer MA, and threshold with color-coded formatting.
🔶 Performance Optimization Framework
Employs efficient calculation methods with null-safe division functions, optimized array management for capsule storage, and conditional plotting minimizing unnecessary rendering. The system includes streamlined weighted average calculation skipping NA metrics, smart capsule cleanup maintaining maximum limit through oldest-first deletion, and minimal recalculation overhead through var declarations and confirmed bar logic.
This indicator delivers sophisticated Bitcoin-specific valuation analysis through multi-metric on-chain synthesis unavailable in traditional technical indicators. By combining SOPR (profit/loss behavior), MVRV (cost basis valuation), Price-to-Realized (pure valuation), and Mayer Multiple (technical context) into unified cycle framework with statistical normalization, it provides comprehensive market cycle assessment grounded in blockchain fundamentals. The six-tier zone system maps directly to Bitcoin's characteristic 4-year halving cycles with Bottom Extreme zones historically marking generational buying opportunities and Top Extreme zones marking distribution phases. Perfect for long-term Bitcoin investors seeking data-driven cycle timing, position sizing based on valuation extremes (increase allocation in Cold/Bottom zones, reduce in Hot/Top zones), and objective framework for navigating Bitcoin's volatile multi-year cycles with alerts providing advance warning of major cycle transitions requiring portfolio reassessment. مؤشر
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Code 33 - 3 qts of acceleration (YoY) for EPS, Sales, & MarginsMark Minervini's Code 33 screen, from his "Trade Like a Stock Market Wizard" book, helped him look for potentially powerful growth stocks that have 3 straight quarters of EPS (diluted) + Sales + NPMs growth on a YoY basis. I figured I create and share it as a script because as far as I know, TradingView lacks the ability to screen for fundamental acceleration, which here would be defined as consecutive quarterly growth on a YoY comparison basis (comparing Q1 of 2025 to Q1 of 2024; not comparing Q1 of 2025 to Q4 of 2024).
Acceleration is a trademark for techno-fundamentalists such as Minervini, O'Neil, Weinstein, and the list goes on. Now, you will not only be able to see this on your charts, but you can also use this on the Pine Beta Screener to filter for stocks that meet one or more of the criteria. Just set the filter condition to equal "1".
*A quick note on the code: TradingView doesn't have a native 'Net Profit Margin' identifier that isolates strict Fiscal Quarter (FQ) data without smoothing it into a Trailing Twelve Months (TTM) format. Because true YoY acceleration requires raw quarterly comparisons, I coded the script to manually calculate the exact quarterly margin by dividing FQ Net Income by FQ Total Revenue. This ensures the YoY acceleration signal is 100% accurate to the specific quarter.
I am not a coder by any means but I always wanted to have this available to me so after playing around with Gemini's pro LM, you should be able to see and screen stocks like this going forward. Maybe in the future, I will edit it for aesthetic purposes or add more to allow for even more detailed screening especially for CANSLIM investors like myself. I also made it open-source as well so if you prefer different metrics, it should not be too difficult to take this script into a LM of your choice and make it your own.
Happy trading.
NYSE:ASX مؤشر
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Open Interest RSI [BackQuant]Open Interest RSI
A multi-venue open interest oscillator that aggregates OI across major derivatives exchanges, converts it to coin or USD terms, and runs an RSI-style engine on that aggregated OI so you can track positioning pressure, crowding, and mean reversion in leverage flows, not just in price.
What this is
This tool is an RSI built on top of aggregated open interest instead of price. It pulls futures OI from several major exchanges, converts it into a unified unit (COIN or USD), sums it into a single synthetic OI candle, then applies RSI and smoothing to that combined series.
You can then render that Open Interest RSI in different visual modes:
Clean line or colored line for classic oscillator-style reads.
Column-style oscillator for impulse and compression views.
Flag mode that fills between OI RSI and its EMA for trend/mean reversion blends. See:
Heatmap mode that paints the panel based on OI RSI extremes, ideal for scanning. See:
On top of that it includes:
Aggregated OI source selection (Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit).
Choice of OI units (COIN or USD).
Reference lines and OB/OS zones.
Extreme highlighting for either trend or mean reversion.
A vertical OI RSI meter that acts as a quick strength gauge.
Aggregated open interest source
Under the hood, the indicator builds a synthetic open interest candle by:
Looping over a list of supported exchanges: Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Looping over multiple contract suffixes (such as USDT.P, USD.P, USDC.P, USD.PM) to capture different contract types on each venue.
Requesting OI candles from each venue + contract combination for the same underlying symbol.
Converting each OI stream into a common unit: In COIN mode, everything is normalized into coin-denominated OI. In USD mode, coin OI is multiplied by price to approximate notional OI.
Summing up open, high, low and close of OI across venues into a single aggregated OI candle.
If no valid OI is available for the current symbol across all sources, the script throws a clear runtime error so you know you are on an unsupported market.
This gives you a single, exchange-agnostic open interest curve instead of being tied to one venue. That aggregated OI is then passed into the RSI logic.
How the OI RSI is calculated
The RSI side is straightforward, but it is applied to the aggregated OI close:
Compute a base RSI of aggregated OI using the Calculation Period .
Apply a simple moving average of length Smoothing Period (SMA) to reduce noise in the raw OI RSI.
Optionally apply an EMA on top of the smoothed OI RSI as a moving average signal line.
Key parameters:
Calculation Period – base RSI length for OI.
Smoothing Period (SMA) – extra smoothing on the RSI value.
EMA Period – EMA length on the smoothed OI RSI.
The result is:
oi_rsi – raw RSI of aggregated OI.
oi_rsi_s – SMA-smoothed OI RSI.
ma – EMA of the smoothed OI RSI.
Thresholds and extremes
You control three core thresholds:
Mid Point – central reference level, typically 50.
Extreme Upper Threshold – high-level OI RSI edge (for example 80).
Extreme Lower Threshold – low-level OI RSI edge (for example 20).
These thresholds are used for:
Reference lines or OB/OS zone fills.
Heatmap gradient bounds.
Background highlighting of extremes.
The Extreme Highlighting mode controls how extremes are interpreted:
None – do nothing special in extreme regions.
Mean-Rev – background turns red on high OI RSI and green on low OI RSI, framing extremes as contrarian zones.
Trend – background turns green on high OI RSI and red on low OI RSI, framing extremes as participation zones aligned with the prevailing move.
Reference lines and OB/OS zones
You can choose:
None – clean plotting without guides.
Basic Reference Lines – mid, upper and lower thresholds as simple gray horizontals.
OB/OS Levels – filled zones between:
Upper OB: from the upper threshold to 100, colored with the short/overbought color.
Lower OS: from 0 to the lower threshold, colored with the long/oversold color.
These guides help visually anchor the OI RSI within "normal" versus "extreme" regions.
Plotting modes
The Plotting Type input controls how OI RSI is drawn. All modes share the same underlying OI and RSI logic, but emphasise different aspects of the signal.
1) Line mode
This is the classic oscillator representation:
Plots the smoothed OI RSI as a simple line using RSI Line Color and RSI Line Width .
Optionally plots the EMA overlay on the same panel.
Works well when you want standard RSI-style signals on leverage flows: crosses of the midline, divergences versus price, and so on.
2) Colored Line mode
In this mode:
The OI RSI is plotted as a line, but its color is dynamic.
If the smoothed OI RSI is above the mid point, it uses the Long/OB Color .
If it is below the mid point, it uses the Short/OS Color .
This creates an instant visual regime switch between "bullish positioning pressure" and "bearish positioning pressure", while retaining the feel of a traditional RSI line.
3) Oscillator mode
Oscillator mode renders OI RSI as vertical columns around the mid level:
The smoothed OI RSI is plotted as columns using plot.style_columns .
The histogram base is fixed at 50, so bars extend above and below the mid line.
Bar color is dynamic, using long or short colors depending on which side of the mid point the value sits.
This representation makes impulse and compression in OI flows more obvious. It is especially useful when you want to focus on how quickly OI RSI is expanding or contracting around its neutral level. See:
4) Flag mode
Flag mode turns OI RSI and its EMA into a two-line band with a filled area between them:
The smoothed OI RSI and its EMA are both plotted.
A fill is drawn between them.
The fill color flips between the long color and the short color depending on whether OI RSI is above or below its EMA.
Black outlines are added to both lines to make the band clear against any background.
This creates a "flag" style region where:
Green fills show OI RSI leading its EMA, suggesting positive positioning momentum.
Red fills show OI RSI trailing below its EMA, suggesting negative positioning momentum.
Crossovers of the two lines can be read as shifts in OI momentum regime.
Flag mode is useful if you want a more structural view that combines both the level and slope behaviour of OI RSI. See:
5) Heatmap mode
Heatmap mode recasts OI RSI as a single-row gradient instead of a line:
A single row at level 1 is plotted using column style.
The color is pulled from a gradient between the lower and upper thresholds: Near the lower threshold it approaches the short/oversold color and near the upper threshold it approaches the long/overbought color.
The EMA overlay and reference lines are disabled in this mode to keep the panel clean.
This is a very compact way to track OI RSI state at a glance, especially when stacking it alongside other indicators. See:
OI RSI vertical meter
Beyond the main plot, the script can draw a small "thermometer" table showing the current OI RSI position from 0 to 100:
The meter is a two-column table with a configurable number of rows.
Row colors form an inverted gradient: red at the top (100) and green at the bottom (0).
The script clamps OI RSI between 0 and 100 and maps it to a row index.
An arrow marker "▶" is drawn next to the row corresponding to the current OI RSI value.
0 and 100 labels are printed at the ends of the scale for orientation.
You control:
Show OI RSI Meter – turn the meter on or off.
OI RSI Blocks – number of vertical blocks (granularity).
OI RSI Meter Position – panel anchor (top/bottom, left/center/right).
The meter is particularly helpful if you keep the main plot in a small panel but still want an intuitive strength gauge.
How to read it as a market pressure gauge
Because this is an RSI built on aggregated open interest, its extremes and regimes speak to positioning pressure rather than price alone:
High OI RSI (near or above the upper threshold) indicates that open interest has been increasing aggressively relative to its recent history. This often coincides with crowded leverage and a buildup of directional pressure.
Low OI RSI (near or below the lower threshold) indicates aggressive de-leveraging or closing of positions, often associated with flushes, forced unwinds or post-liquidation clean-ups.
Values around the mid point indicate more balanced positioning flows.
You can combine this with price action:
Price up with rising OI RSI suggests fresh leverage joining the move, a more persistent trend.
Price up with falling OI RSI suggests shorts covering or longs taking profit, more fragile upside.
Price down with rising OI RSI suggests aggressive new shorts or levered selling.
Price down with falling OI RSI suggests de-leveraging and potential exhaustion of the move.
Trading applications
Trend confirmation on leverage flows
Use OI RSI to confirm or question a price trend:
In an uptrend, rising OI RSI with values above the mid point indicates supportive leverage flows.
In an uptrend, repeated failures to lift OI RSI above mid point or persistent weakness suggest less committed participation.
In a downtrend, strong OI RSI on the downside points to aggressive shorting.
Mean reversion in positioning
Use thresholds and the Mean-Rev highlight mode:
When OI RSI spends extended time above the upper threshold, the crowd is extended on one side. That can set up squeeze risk in the opposite direction.
When OI RSI has been pinned low, it suggests heavy de-leveraging. Once price stabilises, a re-risking phase is often not far away.
Background colours in Mean-Rev mode help visually identify these periods.
Regime mapping with plotting modes
Different plotting modes give different perspectives:
Heatmap mode for dashboard-style use where you just need to know "hot", "neutral" or "cold" on OI flows at a glance.
Oscillator mode for short term impulses and compression reads around the mid line. See:
Flag mode for blending level and trend of OI RSI into a single banded visual. See:
Settings overview
RSI group
Plotting Type – None, Line, Colored Line, Oscillator, Flag, Heatmap.
Calculation Period – base RSI length for OI.
Smoothing Period (SMA) – smoothing on RSI.
Moving Average group
Show EMA – toggle EMA overlay (not used in heatmap).
EMA Period – length of EMA on OI RSI.
EMA Color – colour of EMA line.
Thresholds group
Mid Point – central reference.
Extreme Upper Threshold and Extreme Lower Threshold – OB/OS thresholds.
Select Reference Lines – none, basic lines or OB/OS zone fills.
Extreme Highlighting – None, Mean-Rev, Trend.
Extra Plotting and UI
RSI Line Color and RSI Line Width .
Long/OB Color and Short/OS Color .
Show OI RSI Meter , OI RSI Blocks , OI RSI Meter Position .
Open Interest Source
OI Units – COIN or USD.
Exchange toggles: Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Notes
This is a positioning and pressure tool, not a complete system. It:
Models aggregated futures open interest across multiple centralized exchanges.
Transforms that OI into an RSI-style oscillator for better comparability across regimes.
Offers several visual modes to match different workflows, from detailed analysis to compact dashboards.
Use it to understand how leverage and positioning are evolving behind the price, to gauge when the crowd is stretched, and to decide whether to lean with or against that pressure. Attach it to your existing signals, not in place of them.
Also, please check out @NoveltyTrade for the OI Aggregation logic & pulling the data source!
Here is the original script:
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Quick Valuation V.1.0 (Ibo)This Pine Script indicator performs a Quick Discounted Cash Flow (DCF)-style Valuation to estimate the intrinsic value of a stock.
It calculates a projected Fair Value and a Margin of Safety based on user inputs or automatically pulled financial data from TradingView (like revenue, growth, margin, and exit P/E). It also automatically computes a Discount Rate using a modified CAPM model.
Key Features
Valuation Output: Calculates a target Fair Value and the resulting Margin of Safety.
Data Flexibility: Automatically pulls essential fundamentals (Revenue, Margins, Shares Outstanding, etc.) but allows the user to override any value (revenue, growth, P/E, shares, etc.) via the settings.
Automated Discount Rate: Calculates the Discount Rate (Cost of Equity) using the current 10-Year Real Yield and a computed or user-defined Beta.
Clear Display: Presents all input metrics, calculated values, and data sources (TradingView or User Input) in a neat table on the chart. مؤشر
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MVRV Ratio [Alpha Extract]The MVRV Ratio Indicator provides valuable insights into Bitcoin market cycles by tracking the relationship between market value and realized value. This powerful on-chain metric helps traders identify potential market tops and bottoms, offering clear buy and sell signals based on historical patterns of Bitcoin valuation.
🔶 CALCULATION The indicator processes MVRV ratio data through several analytical methods:
Raw MVRV Data: Collects MVRV data directly from INTOTHEBLOCK for Bitcoin
Optional Smoothing: Applies simple moving average (SMA) to reduce noise
Status Classification: Categorizes market conditions into four distinct states
Signal Generation: Produces trading signals based on MVRV thresholds
Price Estimation: Calculates estimated realized price (Current price / MVRV ratio)
Historical Context: Compares current values to historical extremes
Formula:
MVRV Ratio = Market Value / Realized Value
Smoothed MVRV = SMA(MVRV Ratio, Smoothing Length)
Estimated Realized Price = Current Price / MVRV Ratio
Distance to Top = ((3.5 / MVRV Ratio) - 1) * 100
Distance to Bottom = ((MVRV Ratio / 0.8) - 1) * 100
🔶 DETAILS Visual Features:
MVRV Plot: Color-coded line showing current MVRV value (red for overvalued, orange for moderately overvalued, blue for fair value, teal for undervalued)
Reference Levels: Horizontal lines indicating key MVRV thresholds (3.5, 2.5, 1.0, 0.8)
Zone Highlighting: Background color changes to highlight extreme market conditions (red for potentially overvalued, blue for potentially undervalued)
Information Table: Comprehensive dashboard showing current MVRV value, market status, trading signal, price information, and historical context
Interpretation:
MVRV ≥ 3.5: Potential market top, strong sell signal
MVRV ≥ 2.5: Overvalued market, consider selling
MVRV 1.5-2.5: Neutral market conditions
MVRV 1.0-1.5: Fair value, consider buying
MVRV < 1.0: Potential market bottom, strong buy signal
🔶 EXAMPLES
Market Top Identification: When MVRV ratio exceeds 3.5, the indicator signals potential market tops, highlighting periods where Bitcoin may be significantly overvalued.
Example: During bull market peaks, MVRV exceeding 3.5 has historically preceded major corrections, helping traders time their exits.
Bottom Detection: MVRV values below 1.0, especially approaching 0.8, have historically marked excellent buying opportunities.
Example: During bear market bottoms, MVRV falling below 1.0 has identified the most profitable entry points for long-term Bitcoin accumulation.
Tracking Market Cycles: The indicator provides a clear visualization of Bitcoin's market cycles from undervalued to overvalued states.
Example: Following the progression of MVRV from below 1.0 through fair value and eventually to overvalued territory helps traders position themselves appropriately throughout Bitcoin's market cycle.
Realized Price Support: The estimated realized price often acts as a significant
support/resistance level during market transitions.
Example: During corrections, price often finds support near the realized price level calculated by the indicator, providing potential entry points.
🔶 SETTINGS
Customization Options:
Smoothing: Toggle smoothing option and adjust smoothing length (1-50)
Table Display: Show/hide the information table
Table Position: Choose between top right, top left, bottom right, or bottom left positions
Visual Elements: All plots, lines, and background highlights can be customized for color and style
The MVRV Ratio Indicator provides traders with a powerful on-chain metric to identify potential market tops and bottoms in Bitcoin. By tracking the relationship between market value and realized value, this indicator helps identify periods of overvaluation and undervaluation, offering clear buy and sell signals based on historical patterns. The comprehensive information table delivers valuable context about current market conditions, helping traders make more informed decisions about market positioning throughout Bitcoin's cyclical patterns.
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FA Dashboard: Valuation, Profitability & SolvencyFundamental Analysis Dashboard: A Multi-Dimensional View of Company Quality
This script presents a structured and customizable dashboard for evaluating a company’s fundamentals across three key dimensions: Valuation, Profitability, and Solvency & Liquidity.
Unlike basic fundamental overlays, this dashboard consolidates multiple financial indicators into visual tables that update dynamically and are grouped by category. Each ratio is compared against configurable thresholds, helping traders quickly assess whether a company meets certain value investing criteria. The tables use color-coded checkmarks and fail marks (✔️ / ❌) to visually signal pass/fail evaluations.
▶️ Key Features
Valuation Ratios:
Earnings Yield: EBIT / EV
EV / EBIT and EV / FCF: Enterprise value metrics for profitability
Price-to-Book, Free Cash Flow Yield, PEG Ratio
Profitability Ratios:
Return on Invested Capital (ROIC), ROE, Operating, Net & Gross Margins, Revenue Growth
Solvency & Liquidity Ratios:
Debt to Equity, Debt to EBITDA, Current Ratio, Quick Ratio, Altman Z-Score
Each of these metrics is calculated using request.financial() and can be viewed using either annual (FY) or quarterly (FQ) data, depending on user preference.
🧠 How to Use
Add the script to any stock chart.
Select your preferred data period (FY or FQ).
Adjust thresholds if desired to match your personal investing strategy.
Review the visual dashboard to see which metrics the company passes or fails.
💡 Why It’s Useful
This tool is ideal for traders or long-term investors looking to filter stocks using fundamental criteria. It draws inspiration from principles used by Benjamin Graham, Warren Buffett, and Joel Greenblatt, offering a fast and informative way to screen quality businesses.
This is not a repackaged built-in or autogenerated script. It’s a custom-built, interactive tool tailored for fundamental analysis using official financial data provided via Pine Script’s request.financial().
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TradFi Fundamentals: Momentum Trading with Macroeconomic DataIntroduction
This indicator combines traditional price momentum with key macroeconomic data. By retrieving GDP, inflation, unemployment, and interest rates using security calls, the script automatically adapts to the latest economic data. The goal is to blend technical analysis with fundamental insights to generate a more robust momentum signal.
Original Research Paper by Mohit Apte, B. Tech Scholar, Department of Computer Science and Engineering, COEP Technological University, Pune, India
Link to paper
Explanation
Price Momentum Calculation:
The indicator computes price momentum as the percentage change in price over a configurable lookback period (default is 50 days). This raw momentum is then normalized using a rolling simple moving average and standard deviation over a defined period (default 200 days) to ensure comparability with the economic indicators.
Fetching and Normalizing Economic Data:
Instead of manually inputting economic values, the script uses TradingView’s security function to retrieve:
GDP from ticker "GDP"
Inflation (CPI) from ticker "USCCPI"
Unemployment rate from ticker "UNRATE"
Interest rates from ticker "USINTR"
Each series is normalized over a configurable normalization period (default 200 days) by subtracting its moving average and dividing by its standard deviation. This standardization converts each economic indicator into a z-score for direct integration into the momentum score.
Combined Momentum Score:
The normalized price momentum and economic indicators are each multiplied by user-defined weights (default: 50% price momentum, 20% GDP, and 10% each for inflation, unemployment, and interest rates). The weighted components are then summed to form a comprehensive momentum score. A horizontal zero line is plotted for reference.
Trading Signals:
Buy signals are generated when the combined momentum score crosses above zero, and sell signals occur when it crosses below zero. Visual markers are added to the chart to assist with trade timing, and alert conditions are provided for automated notifications.
Settings
Price Momentum Lookback: Defines the period (in days) used to compute the raw price momentum.
Normalization Period for Price Momentum: Sets the window over which the price momentum is normalized.
Normalization Period for Economic Data: Sets the window over which each macroeconomic series is normalized.
Weights: Adjust the influence of each component (price momentum, GDP, inflation, unemployment, and interest rate) on the overall momentum score.
Conclusion
This implementation leverages TradingView’s economic data feeds to integrate real-time macroeconomic data into a momentum trading strategy. By normalizing and weighting both technical and economic inputs, the indicator offers traders a more holistic view of market conditions. The enhanced momentum signal provides additional context to traditional momentum analysis, potentially leading to more informed trading decisions and improved risk management.
The next script I release will be an improved version of this that I have added my own flavor to, improving the signals. مؤشر
Blockchain Fundamentals: Liquidity & BTC YoYLiquidity & BTC YoY Indicator
Overview:
This indicator calculates the Year-over-Year (YoY) percentage change for two critical metrics: a custom Liquidity Index and Bitcoin's price. The Liquidity Index is derived from a blend of economic and forex data representing the M2 money supply, while the BTC price is obtained from a reliable market source. A dedicated limit(length) function is implemented to handle limited historical data, ensuring that the YoY calculations are available immediately—even when the chart's history is short.
Features Breakdown:
1. Limited Historical Data Workaround
- Functionality: limit(length) The function dynamically adjusts the lookback period when there isn’t enough historical data. This prevents delays in displaying YoY metrics at the beginning of the chart.
2. Liquidity Calculation
- Data Sources: Combines multiple data streams:
USM2, ECONOMICS:CNM2, USDCNY, ECONOMICS:JPM2, USDJPY, ECONOMICS:EUM2, USDEUR
- Formula:
Liquidity Index = USM2 + (CNM2 / USDCNY) + (JPM2 / USDJPY) + (EUM2 / USDEUR)
[b3. Bitcoin Price Calculation
- Data Source: Retrieves Bitcoin's price from BITSTAMP:BTCUSD on the user-selected timeframe for its historical length.
4. Year-over-Year (YoY) Percent Change Calculation
- Methodology:
- The indicator uses a custom function, to autodetect the proper number of bars, based on the selected timeframe.
- It then compares the current value to that from one year ago for both the Liquidity Index and BTC price, calculating the YoY percentage change.
5. Visual Presentation
- Plotting:
- The YoY percentage changes for Liquidity (plotted in blue) and BTC price (plotted in orange) are clearly displayed.
- A horizontal zero line is added for visual alignment, making it easier to compare the two copies of the metric. You add one copy and only display the BTC YoY. Then you add another copy and only display the M2 YoY.
-The zero lines are then used to align the scripts to each other by interposing them. You scale each chart the way you like, then move each copy individually to align both zero lines on top of each other.
This indicator is ideal for analysts and investors looking to monitor macroeconomic liquidity trends alongside Bitcoin's performance, providing immediate insights. مؤشر
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CAPE / Shiller PE RatioThe CAPE (Cyclically Adjusted Price-to-Earnings) or Shiller PE ratio is a popular valuation measure used by investors to assess whether a stock or index is over or undervalued relative to its historical earnings. Unlike the traditional P/E ratio, the CAPE ratio smooths earnings over ten years, adjusting for inflation and providing a more stable and long-term view of valuation.
This indicator lets you quickly calculate and visualize the CAPE ratio for any stock on TradingView, helping you make informed decisions about the sustainability of current price levels. With its clear presentation and intuitive setup, you can compare historical CAPE levels and identify potential opportunities for long-term investments or avoid overvalued markets.
Advantages of the CAPE Ratio:
Long-Term Focus : Smooth earnings over ten years, reducing the impact of short-term volatility.
Inflation-Adjusted : Provides a more precise, inflation-adjusted valuation measure over time.
Historical Comparison : Allows for benchmarking against long-term historical averages.
Market Sentiment Indicator : Can highlight overvalued or undervalued markets for long-term investors.
Reduces Noise : Filters out short-term earnings fluctuations, offering a more stable view.
Disadvantages of the CAPE Ratio:
Ignores Recent Earnings : Misses short-term earnings changes, which can affect current valuations.
Outdated Data : Relies on old earnings data that may not reflect recent company performance.
Less Effective for Growth Stocks : May undervalue high-growth stocks focused on future earnings.
Sector Limitations : Works best for broad markets, less so for fast-changing industries.
Debated Predictive Power : It’s unreliable for timing short-term market movements.
In short, the CAPE ratio is excellent for long-term valuation but has limitations for short-term or growth-focused investing.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice. مؤشر
