Peter Lynch Value (Dynamic Growth)This indicator implements Peter Lynch's core valuation principle: Fair Price = Earnings Per Share (EPS) * Growth Rate.
It provides a dynamic "fair value" line overlaid on the price chart, allowing traders and investors to quickly assess whether a stock's current price is trading above or below its intrinsic value according to the Lynch method.
Key Features
1. Dynamic Growth Rate Calculation
The indicator uses a custom algorithm to calculate the critical EPS Growth Rate, making it robust against missing data from standard financial fields.
Methodology: It fetches historical TTM Diluted EPS reports (EARNINGS_PER_SHARE_DILUTED, TTM) and calculates the Year-over-Year (YoY) Growth Percentage from the current TTM value versus the TTM value 4 periods prior.
Reliability: This custom calculation ensures the value line appears even when TradingView's pre-calculated growth metrics are unavailable (na).
2. Multiplier Control
P/E Cap: You can enforce a maximum P/E multiplier (maxPE, default 25), preventing the fair value from becoming unrealistically high for extremely fast-growing companies (as Lynch suggested).
Fallback P/E: If insufficient financial history is available to calculate the growth rate, the indicator automatically switches to a user-defined fallbackPE (default 15) and highlights the line in orange as a warning.
3. Smoothing (Optional)
To reduce the volatility often seen in valuation metrics, you can apply an optional Simple Moving Average (SMA) to the Fair Value line. This helps visualize the underlying trend of intrinsic value.
4. Forward Estimate (Optional)
Display an optional projection (circles) based on the analysts' next Fiscal Year EPS Estimate (EARNINGS_ESTIMATE, FY). This shows the potential fair value if the company meets future expectations.
5. Diagnostic Table
A table in the corner provides transparency on the calculation:
Green/Red: Confirms if TTM EPS and Calculated Growth are found.
Final P/E Used: Shows the exact multiplier used (calculated growth or the manual fallback).
Disclaimer: This tool is for informational and educational purposes only and should not be considered financial advice.
Kazançlar
PEAD ScreenerPEAD Screener - Post-Earnings Announcement Drift Scanner
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WHY EARNINGS ANNOUNCEMENTS CREATE OPPORTUNITY
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The days immediately following an earnings announcement are among the noisiest periods for any stock. Within hours, the market must digest new information about a company's profits, revenue, and future outlook. Analysts scramble to update their models. Institutions rebalance positions. Retail traders react to headlines.
This chaos creates a well-documented phenomenon called Post-Earnings Announcement Drift (PEAD): stocks that beat expectations tend to keep rising, while those that miss tend to keep falling - often for weeks after the initial announcement. Academic research has confirmed this pattern persists across decades and markets.
But not every earnings surprise is equal. A company that beats estimates by 5 cents might move very differently than one that beats by 5 cents with unusually high volume, or one where both earnings AND revenue exceeded expectations. Raw numbers alone don't tell the full story.
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HOW "STANDARDIZED UNEXPECTED" METRICS CUT THROUGH THE NOISE
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This screener uses a statistical technique to measure how "surprising" a result truly is - not just whether it beat or missed, but how unusual that beat or miss was compared to the company's own history.
The core idea: convert raw surprises into Z-scores.
A Z-score answers the question: "How many standard deviations away from normal is this result?"
- A Z-score of 0 means the result was exactly average
- A Z-score of +2 means the result was unusually high (better than ~95% of historical results)
- A Z-score of -2 means the result was unusually low
By standardizing surprises this way, we can compare apples to apples. A small-cap biotech's $0.02 beat might actually be more significant than a mega-cap's $0.50 beat, once we account for each company's typical variability.
This screener applies this standardization to three dimensions: earnings (SUE), revenue (SURGE), and volume (SUV).
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THE 9 SCREENING CRITERIA
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1. SUE (Standardized Unexpected Earnings)
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WHAT IT IS:
SUE measures how surprising an earnings result was, adjusted for the company's historical forecast accuracy.
Calculation: Take the earnings surprise (actual EPS minus analyst estimate), then divide by the standard deviation of past forecast errors. This uses a rolling window of the last 8 quarters by default.
Formula: SUE = (Actual EPS - Estimated EPS) / Standard Deviation of Past Errors
HOW TO INTERPRET:
- SUE > +2.0: Strongly positive surprise - earnings beat expectations by an unusually large margin. These stocks often continue drifting higher.
- SUE between 0 and +2.0: Modest positive surprise - beat expectations, but within normal range.
- SUE between -2.0 and 0: Modest negative surprise - missed expectations, but within normal range.
- SUE < -2.0: Strongly negative surprise - significant miss. These stocks often continue drifting lower.
For long positions, look for SUE values above +2.0, ideally combined with positive SURGE.
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2. SURGE (Standardized Unexpected Revenue)
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WHAT IT IS:
SURGE applies the same standardization technique to revenue surprises. While earnings can be manipulated through accounting choices, revenue is harder to fake - it represents actual sales.
Calculation: Take the revenue surprise (actual revenue minus analyst estimate), then divide by the standard deviation of past revenue forecast errors.
Formula: SURGE = (Actual Revenue - Estimated Revenue) / Standard Deviation of Past Errors
HOW TO INTERPRET:
- SURGE > +1.5: Strongly positive revenue surprise - the company sold significantly more than expected.
- SURGE between 0 and +1.5: Modest positive surprise.
- SURGE < 0: Revenue missed expectations.
The most powerful signals occur when BOTH SUE and SURGE are positive and elevated (ideally SUE > 2.0 AND SURGE > 1.5). This indicates the company beat on both profitability AND top-line growth - a much stronger signal than either alone.
When SUE and SURGE diverge significantly (e.g., high SUE but negative SURGE), treat with caution - the earnings beat may have come from cost-cutting rather than genuine growth.
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3. SUV (Standardized Unexpected Volume)
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WHAT IT IS:
SUV detects unusual trading volume after accounting for how volatile the stock is. More volatile stocks naturally have higher volume, so raw volume comparisons can be misleading.
Calculation: This uses regression analysis to model the expected relationship between price volatility and volume. The "unexpected" volume is the residual - how much actual volume deviated from what the model predicted. This residual is then standardized into a Z-score.
In plain terms: SUV asks "Given how much this stock typically moves, is today's volume unusually high or low?"
HOW TO INTERPRET:
- SUV > +2.0: Exceptionally high volume relative to the stock's volatility. This often signals institutional activity - big players moving in or out.
- SUV between +1.0 and +2.0: Elevated volume - above normal interest.
- SUV between -1.0 and +1.0: Normal volume range.
- SUV < -1.0: Unusually quiet - less activity than expected.
High SUV combined with positive price movement suggests accumulation (buying). High SUV combined with negative price movement suggests distribution (selling).
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4. % From D0 Close
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WHAT IT IS:
This measures how far the current price has moved from the closing price on its initial earnings reaction day (D0). The "reaction day" is the first trading day that fully reflects the earnings news - typically the day after an after-hours announcement, or the announcement day itself for pre-market releases.
Calculation: ((Current Price - D0 Close) / D0 Close) × 100
HOW TO INTERPRET:
- Positive values: Stock has gained ground since earnings. The higher the percentage, the stronger the post-earnings drift.
- 0% to +5%: Modest positive drift - earnings were received well but momentum is limited.
- +5% to +15%: Strong drift - buyers continue accumulating.
- > +15%: Exceptional drift - significant institutional interest likely.
- Negative values: Stock has given back gains or extended losses since earnings. May indicate the initial reaction was overdone, or that sentiment is deteriorating.
This metric is most meaningful within the first 5-20 trading days after earnings. Extended drift (maintaining gains over 2+ weeks) is a stronger signal than a quick spike that fades.
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5. # Pocket Pivots
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WHAT IT IS:
Pocket Pivots are a volume-based pattern developed by Chris Kacher and Gil Morales. They identify days where institutional buyers are likely accumulating shares without causing obvious breakouts.
Calculation: A Pocket Pivot occurs when:
- The stock closes higher than it opened (up day)
- The stock closes higher than the previous day's close
- Today's volume exceeds the highest down-day volume of the prior 10 trading sessions
The screener counts how many Pocket Pivots have occurred since the earnings announcement.
HOW TO INTERPRET:
- 0 Pocket Pivots: No detected institutional accumulation patterns since earnings.
- 1-2 Pocket Pivots: Some institutional buying interest - worth monitoring.
- 3+ Pocket Pivots: Strong accumulation signal - institutions appear to be building positions.
Pocket Pivots are most significant when they occur:
- Immediately following earnings announcements
- Near moving average support (10-day, 21-day, or 50-day)
- On above-average volume
- After a period of price consolidation
Multiple Pocket Pivots in a short period suggest sustained institutional demand, not just a one-day event.
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6. ADX/DI (Trend Strength and Direction)
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WHAT IT IS:
ADX (Average Directional Index) measures trend strength regardless of direction. DI (Directional Indicator) shows whether the trend is bullish or bearish.
Calculation: ADX uses a 14-period lookback to measure how directional (trending) price movement is. Values range from 0 to 100. The +DI and -DI components compare upward and downward movement.
The screener shows:
- ADX value (trend strength)
- Direction indicator: "+" for bullish (price trending up), "-" for bearish (price trending down)
HOW TO INTERPRET:
- ADX < 20: Weak trend - the stock is moving sideways, choppy. Not ideal for momentum trading.
- ADX 20-25: Trend is emerging - potentially starting a directional move.
- ADX 25-40: Strong trend - clear directional movement. Good for momentum plays.
- ADX > 40: Very strong trend - powerful move in progress, but may be extended.
The direction indicator (+/-) tells you which way:
- "25+" means ADX of 25 with bullish direction (uptrend)
- "25-" means ADX of 25 with bearish direction (downtrend)
For post-earnings plays, ideal setups show ADX rising above 25 with positive direction, confirming the earnings reaction is developing into a sustained trend rather than a one-day spike.
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7. Institutional Buying PASS
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WHAT IT IS:
This proprietary composite indicator detects patterns consistent with institutional accumulation at three stages after earnings:
EARLY (Days 0-4): Looks for "large block" buying on the earnings reaction day (exceptionally high volume with a close in the upper half of the day's range) combined with follow-through buying on the next day.
MID (Days 5-9): Checks for sustained elevated volume (averaging 1.5x the 20-day average) combined with positive drift and consistent upward price movement (more up days than down days).
LATE (Days 10+): Detects either visible accumulation (positive drift with high volume) OR stealth accumulation (positive drift with unusually LOW volume - suggesting smart money is quietly building positions without attracting attention).
HOW TO INTERPRET:
- Check mark/value of '1': Institutional buying pattern detected. The stock shows characteristics consistent with large players accumulating shares.
- X mark/value of '0': No institutional buying pattern detected. This doesn't mean institutions aren't buying - just that the typical footprints aren't visible.
A passing grade here adds conviction to other bullish signals. Institutions have research teams, information advantages, and long time horizons. When their footprints appear in the data, it often precedes sustained moves.
Important: This is a pattern detection tool, not a guarantee. Always combine with other analysis.
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8. Strong ATR Drift PASS
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WHAT IT IS:
This measures whether the stock has drifted significantly relative to its own volatility. Instead of asking "did it move 10%?", it asks "did it move more than 1.5 ATRs?"
ATR (Average True Range) measures a stock's typical daily movement. A volatile stock might move 5% daily, while a stable stock might move 0.5%. Using ATR normalizes for this difference.
Calculation:
ATR Drift = (Current Close - D0 Close) / D0 ATR in dollars
The indicator passes when ATR Drift exceeds 1.5 AND at least 5 days have passed since earnings.
HOW TO INTERPRET:
- Check mark/value of '1': The stock has drifted more than 1.5 times its average daily range since earnings - a statistically significant move that suggests genuine momentum, not just noise.
- X mark/value of '0': The drift (if any) is within normal volatility bounds - could just be random fluctuation.
Why wait 5 days? The immediate post-earnings reaction (days 0-2) often includes gap fills and noise. By day 5, if the stock is still extended beyond 1.5 ATRs from the earnings close, it suggests real buying pressure, not just a reflexive gap.
A passing grade here helps filter out stocks that "beat earnings" but haven't actually moved meaningfully. It focuses attention on stocks where the market is voting with real capital.
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9. Days Since D0
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WHAT IT IS:
Simply counts the number of trading days since the earnings reaction day (D0).
HOW TO INTERPRET:
- Days 0-5 (Green): Fresh earnings - the information is new, institutional repositioning is active, and momentum trades are most potent. This is the "sweet spot" for PEAD strategies.
- Days 6-10 (Neutral): Mid-period - some edge remains but diminishing. Good for adding to winning positions, less ideal for new entries.
- Days 11+ (Red): Extended period - most of the post-earnings drift has typically played out. Higher risk that momentum fades or reverses.
Research shows PEAD effects are strongest in the first 5-10 days after earnings, then decay. Beyond 20-30 days, the informational advantage of the earnings surprise is largely priced in.
Use this to prioritize: focus on stocks with strong signals that are still in the early window, and be more selective about entries as days accumulate.
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PUTTING IT ALL TOGETHER
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You can use this screener in the chart view or in the Screener.
One combination of the above filters to develop a shortlist of positive drift candidates may be:
- SUE > 2.0 (significant earnings beat)
- SURGE > 1.5 (significant revenue beat)
- Positive % From D0 Close (price confirming the good news)
- Institutional Buying PASS (big players accumulating)
- Strong ATR Drift PASS (statistically significant movement)
- Days Since D0 < 10 (still in the active drift window)
No single indicator is sufficient. The power comes from convergence - when multiple independent measures all point the same direction.
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SETTINGS
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Key adjustable parameters:
- SUE Method: "Analyst-based" uses consensus estimates; "Time-series" uses year-over-year comparison
- Window Size: Number of quarters used for standardization (default: 8)
- ATR Drift Threshold: Minimum ATR multiple for "strong" classification (default: 1.5)
- Institutional Buying thresholds: Adjustable volume and CLV parameters
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DISCLAIMER
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This screener is a research tool, not financial advice. Past patterns do not guarantee future results. Always conduct your own due diligence and manage risk appropriately. Post-earnings trading involves significant uncertainty and volatility. The 'SUE' in this indicator does not represent a real person; any similarity to actual Sue's (or Susans for that matter) living or dead is quite frankly ridiculous, not to mention coincidental.
PEG RSI [Auto EPS Growth]The PEG RSI is a hybrid indicator that combines fundamental valuation with technical momentum. It applies the Relative Strength Index (RSI) directly to the Price/Earnings-to-Growth (PEG) Ratio.
Unlike traditional PEG indicators that require manual input for growth rates, this script automatically calculates the Compound Annual Growth Rate (CAGR) of Earnings Per Share (EPS) based on historical data.
Key Features
- Auto-Calculated Growth: Uses historical TTM Earnings Per Share (EPS) to calculate the CAGR over a user-defined period (Default: 4 years).
- Dynamic Valuation: Converts the static PEG ratio into an oscillator (RSI) to identify relative valuation extremes.
- Trend & Momentum: Visualizes the momentum of the PEG ratio relative to its own history.
Educational Case Study
This indicator is designed for educational purposes and research. Instead of relying on fixed overbought or oversold levels, users are encouraged to study the correlation between the PEG RSI and price action independently.
- Observe how the price reacts when the PEG RSI reaches upper or lower extremes.
- Different stocks may respect different RSI zones based on their growth stability.
- Use this tool to analyze how market valuation momentum shifts over time.
Settings:
- Years for CAGR Growth: Timeframe to calculate EPS growth (Default: 4 years).
- RSI Length: Lookback period for the RSI calculation (Default: 14).
Note: This indicator works best on stocks with a consistent history of earnings. It requires financial data to function (will not work on assets without EPS like Crypto or Forex).
MarketSurge EPS Line [tradeviZion]MarketSurge EPS Line
EPS trend line overlay for TradingView charts, inspired by the IBD MarketSurge (formerly MarketSmith) EPS line style.
Comparison: Left side shows IBD MarketSurge EPS line as reference. Right side shows this TradingView script producing similar output with interactive tooltips. The left side image is for reference only to demonstrate similarity - it is not part of the TradingView script.
Features:
Displays EPS trend line on price charts
Uses 4-quarter earnings moving average
Shows earnings momentum over time
Works with actual, estimated, or standardized earnings data
Customizable line color and width
Interactive tooltips with detailed earnings information
Custom symbol analysis support
How to Use:
Add script to chart
EPS line appears automatically
Adjust color and width in settings if needed
Hover over line for earnings details
Settings Explained:
Display Settings:
Show EPS Line: Toggle to show or hide the EPS trend line
EPS Line Color: Choose the color for the EPS trend line and labels
EPS Line Width: Adjust the thickness of the EPS trend line (1-5 pixels)
Symbol Settings:
By default, the indicator analyzes the EPS data for the symbol currently displayed on your chart. The Custom Symbol feature allows you to:
Analyze EPS data for a different symbol without changing your chart
Compare earnings trends of related stocks or competitors
View EPS data for one symbol while analyzing price action of another
To use Custom Symbol:
Enable "Use Custom Symbol" checkbox
Click on "Custom Symbol" field to open TradingView's symbol picker
Search and select the symbol you want to analyze
The indicator will fetch and display EPS data for the selected symbol
Note: The chart will still show price action for your current symbol, but the EPS line will reflect the custom symbol's earnings data.
Data Settings:
EPS Field: Choose which earnings data source to use:
Actual Earnings: Reported earnings from company financial statements (default). Use this to analyze historical performance based on what companies actually reported.
Estimated Earnings: Analyst consensus forecasts for future quarters. Use this to see what analysts expect and compare expectations with actual results.
Standardized Earnings: Earnings adjusted for comparability across companies. Use this when comparing multiple stocks as it normalizes accounting differences.
Display Scale:
For the indicator to display correctly on the existing chart, it uses its own axis (right scale) by default. However, you can change this, but the view will not look the same. The right scale is recommended for optimal visibility as it allows the EPS line to be clearly visible alongside price action without compression.
Example: EPS line on separate right scale (recommended) - hover over labels to view detailed earnings tooltips
Example: EPS line pinned to Scale A (not recommended - appears as straight line due to small EPS range compared to price)
Example: EPS line displayed in separate pane below price chart
Methodology Credits:
This indicator implements the EPS line visualization methodology developed by Investor's Business Daily (IBD) for their MarketSurge platform (formerly known as MarketSmith). The EPS line concept helps visualize earnings momentum alongside price action, providing a fundamental overlay for technical analysis.
Technical Details:
Designed for daily, weekly, and monthly timeframes
Minimum 4 quarters of earnings data required
Uses TradingView's built-in earnings data
Automatically handles missing or invalid data
This indicator helps you visualize earnings trends alongside price action, providing a fundamental overlay for your technical analysis.
PE Fair ValueIn short, it’s an automated fair value estimator based on the price-to-earnings model, with full manual control if TradingView’s fundamental data is missing.
Summary:
1. Lets the user choose the EPS source – either automatically from TradingView fundamentals (EPS TTM) or a manual value.
2. Attempts to fetch the stock’s P/E ratio (TTM) automatically; if unavailable, it uses a manual fallback P/E.
3. Calculates:
Actual P/E = current price ÷ EPS
Fair Value = EPS × chosen (auto/manual) P/E
Percentage difference between market price and fair value
4. Plots the fair-value line on the chart for visual comparison.
5. Displays a table in the top-right corner showing:
EPS used
Target P/E
Actual P/E
Fair value
Current price
Difference vs fair value (colored green or red)
6. Creates alerts when the stock is trading above or below the calculated fair value.
7. Also plots the current closing price for reference.
Earnings CountdownAdd to a chart to show a text box with how long to next earnings.
Being updated to add functionality from original open source Pine script
Quarterly Earnings - v1This script shows company fundamentals in a TradingView table: Earnings Per Share (EPS), Price-to-Earnings Ratio (P/E, TTM), Sales (in Crores), Operating Margin (OPM %), Return on Assets (ROA %), and Return on Equity (ROE %).
Quarterly Earnings - v1This script shows company fundamentals in a TradingView table: Earnings Per Share (EPS), Price-to-Earnings Ratio (P/E, TTM), Sales (in Crores), Operating Margin (OPM %), Return on Assets (ROA %), and Return on Equity (ROE %).
DCA vs One-ShotCompare a DCA strategy by choosing the payment frequency (daily, weekly, or monthly), and by choosing whether or not to pay on weekends for cryptocurrency. You can add fees and the reference price (opening, closing, etc.).
Quarterly EarningsEarnings Per Share (EPS), Price-to-Earnings Ratio (P/E, TTM), Sales (in Crores), Operating Margin (OPM %), Return on Assets (ROA %), and Return on Equity (ROE %). Each metric includes its absolute value and quarter-over-quarter or year-over-year percentage change.
Quarterly EarningsThis Pine script shows quarterly EPS, Sales, and P/E (TTM-based) in a styled table.
PE Rating by The Noiseless TraderPE Rating by The Noiseless Trader
This script analyzes a symbol’s Price-to-Earnings (P/E) ratio, using Diluted EPS (TTM) fundamentals directly from TradingView.
The script calculates the Price-to-Earnings ratio (P/E) using Diluted EPS (TTM) fundamentals. It then identifies:
PE High → the highest valuation point over a 3-year historical range.
PE Low → the lowest valuation point over a 3-year historical range.
PE Median → the midpoint between the two extremes, offering a fair-value benchmark.
PE (Int) → an additional intermediate low to track more recent undervaluation points. This is calculated based on lowest valuation point over a 1-year historical range
These levels are plotted directly on the chart as horizontal references, with markers showing the exact bars/dates when the extremes occurred. Candles corresponding to those days are also highlighted for context.
Bars corresponding to these extremes are highlighted (red = PE High, green = PE Low).
How it helps
Provides a historical valuation framework that complements technical analysis. We look for long opportunity or base formation near the PE Low and be cautious when stocks tends to trade near High PE.
We do not short the stock at High PE infact be cautious with long trades.
Helps identify whether current price action is happening near overvalued or undervalued zones.
Adds a long-term perspective to support swing trading and investing decisions. If a stock is coming from Low PE to Median PE and along with that if we get entry based on Classical strategies like Darvas Box, or HH-HL based on Dow Theory.
Offers a simple visual map of how far the market has moved from “cheap” to “expensive.”
This tool is best suited for long-term investors and swing traders who want to merge fundamentals with technical setups.
This indicator is designed as an educational tool to illustrate how valuation metrics (like earnings multiples) can be viewed alongside price action, helping traders connect fundamental context with technical execution in real market conditions.
Forward P/E CalculatorI could not find a forward P/E indicator that gave me proper results. So here is mine.
EPS QoQ % ChangeThis indicator calculates and displays the quarter-over-quarter (QoQ) percentage change in earnings per share (EPS) directly on your chart, aligned with each earnings event.
It is designed to quickly highlight EPS growth or decline without the need to open an earnings report, providing traders and investors with instant, visual performance context.
Features :
- Automatic Earnings Detection: Identifies earnings bars and calculates QoQ % change.
- Color-Coded Text: Positive changes are shown in your chosen “up” color, declines in your “down” color, and flat results in a neutral color.
- Customizable Appearance: Choose text size and colors to match your chart style.
- Tooltip Support: Optional detailed tooltip showing reported EPS, previous EPS, and calculated QoQ change.
- Compact Layout: Displays in its own pane to avoid cluttering price action.
Use Cases :
- Quickly assess EPS growth trends over time.
- Spot significant earnings beats or misses without reading earnings transcripts.
- Use alongside other technical or fundamental tools for better decision-making.
EPS+Sales+Net Profit+MCap+Sector & Industry📄 Full Description
This script displays a comprehensive financial data panel directly on your TradingView chart, helping long-term investors and swing traders make informed decisions based on fundamental trends. It consolidates key financial metrics and business classification data into a single, visually clear table.
🔍 Key Features:
🧾 Financial Metrics (Auto-Fetched via request.financial):
EPS (Earnings Per Share) – Displayed with trend direction (QoQ or YoY).
Sales / Revenue – In ₹ Crores (for Indian stocks), trend change also included.
Net Profit – Also in ₹ Crores, along with percentage change.
Market Cap – Automatically calculated using outstanding shares × price, shown in ₹ Cr.
Free Float Market Cap – Based on float shares × price, also in ₹ Cr.
🏷️ Sector & Industry Info:
Automatically identifies and displays the Sector and Industry of the stock using syminfo.sector and syminfo.industry.
Displayed inline with metrics, making it easy to know what business the stock belongs to.
📊 Table View:
Compact and responsive table shown on your chart.
Columns: Date | EPS | QoQ | Sales | QoQ | Net Profit | QoQ | Metrics
Metrics column dynamically shows:
Market Cap
Free Float
Sector (Row 4)
Industry (Row 5)
🌗 Appearance:
Supports Dark Mode and Mini Mode toggle.
You can also customize:
Number of data points (last 4+ quarters or years)
Table position and size
🎯 Use Case:
This script is ideal for:
Fundamental-focused traders who use EPS/Sales trends to identify momentum.
Swing traders who combine price action with fundamental tailwinds.
Portfolio builders who want to see sector/industry alignment quickly.
It works best with fundamentally sound stocks where earnings and profitability are a major factor in price movements.
✅ Important Notes:
Script uses request.financial which only works with supported symbols (mostly stocks).
Market Cap and Free Float are calculated in ₹ Crores.
All financial values are rounded and formatted for readability (e.g., 1,234 Cr).
🙏 Credits:
Developed and published by Sameer Thorappa
Built with a clean, minimalist approach for high readability and functionality.
Earnings [theUltimator5]This indicator highlights daily price changes on earnings announcement days using dynamic colors, labels, and optional earnings markers.
🔍 Key Features:
Earnings Detection:
Highlights only the days when an earnings event occurs.
Price Change Calculation:
Computes the percentage change from open to close on earnings day.
Color-coded Labels:
Displays the % change as a floating label above the chart on earnings days.
Color intensity reflects the size and direction of the move:
Bright green for large gains (≥ +10%)
Bright red for large losses (≤ -10%)
White for negligible change
Gradient fades between those extremes
Optional "Earnings" Marker:
A small label marked “Earnings” appears beneath the % change label, controlled by a user toggle.
Background Highlight:
The chart background is shaded on earnings days with a semi-transparent color based on the % change.
⚙️ User Input:
✅ Show 'E' Marker: Toggles the visibility of the "Earnings" label below the main price change label.
✅ Ideal Use Case:
Use this indicator to visually analyze how a stock reacts on earnings days, helping traders spot consistent behavior patterns (e.g., post-earnings rallies or selloffs).
Greer Value Yields Line📈 Greer Value Yields Line – Valuation Signal Without the Clutter
Part of the Greer Financial Toolkit, this streamlined indicator tracks four valuation-based yield metrics and presents them clearly via the Data Window, GVY Score badge, and an optional Yield Table:
Earnings Yield (EPS ÷ Price)
FCF Yield (Free Cash Flow ÷ Price)
Revenue Yield (Revenue per Share ÷ Price)
Book Value Yield (Book Value per Share ÷ Price)
✅ Each yield is compared against its historical average
✅ A point is scored for each metric above average (0–4 total)
✅ Color-coded GVY Score badge highlights valuation strength
✅ Yield trend-lines Totals (TVAVG & TVPCT) help assess direction
✅ Clean layout: no chart clutter – just actionable insights
🧮 GVY Score Color Coding (0–4):
⬜ 0 = None (White)
⬜ 1 = Weak (Gray)
🟦 2 = Neutral (Aqua)
🟩 3 = Strong (Green)
🟨 4 = Gold Exceptional (All metrics above average)
Total Value Average Line Color Coding:
🟥 Red – Average trending down
🟩 Green – Average trending up
Ideal for long-term investors focused on fundamental valuation, not short-term noise.
Enable the table and badge for a compact yield dashboard — or keep it minimal with just the Data Window and trend-lines.
Greer EPS Yield📘 Script Title
Greer EPS Yield – Valuation Insight Based on Earnings Productivity
🧾 Description
Greer EPS Yield is a valuation-focused indicator from the Greer Financial Toolkit, designed to evaluate how efficiently a company generates earnings relative to its current stock price. This script calculates the Earnings Per Share Yield (EPS%), using the formula:
EPS Yield (%) = Earnings Per Share ÷ Stock Price × 100
This yield metric provides a quick snapshot of valuation through the lens of profitability per share. It dynamically highlights when the EPS yield is:
🟢 Above its historical average (potentially undervalued)
🔴 Below its historical average (potentially overvalued)
🔍 Use Case
Quickly assess valuation attractiveness based on earnings yield.
Identify potential buy opportunities when EPS% is above its long-term average.
Combine with other indicators in the Greer Financial Toolkit for a fundamentals-driven investment strategy:
📘 Greer Value – Tracks year-over-year growth consistency across six key metrics
📊 Greer Value Yields Dashboard – Visualizes valuation-based yield metrics
🟢 Greer BuyZone – Highlights long-term technical buy zones
🛠️ Inputs & Data
Uses fiscal year EPS data from TradingView’s built-in financial database.
Tracks a static average EPS Yield to compare current valuation to historical norms.
Clean, intuitive visual with automatic color coding.
⚠️ Disclaimer
This tool is for educational and informational purposes only and should not be considered financial advice. Always conduct your own research before making investment decisions.
Greer Value Yields Dashboard🧾 Greer Value Yields Dashboard – v1.0
Author: Sean Lee Greer
Release Date: June 22, 2025
🧠 Overview
The Greer Value Yields Dashboard visualizes and evaluates four powerful valuation metrics for any publicly traded company:
📘 Earnings per Share Yield
💵 Free Cash Flow Yield
💰 Revenue Yield
🏦 Book Value Yield
Each yield is measured as a percentage of current stock price and compared against its historical average. The script assigns 1 point per metric when the current yield exceeds its long-term average. The total score (0 to 4) is displayed as a color-coded column chart, helping long-term investors quickly assess fundamental valuation strength.
✅ Key Features
📊 Real-time calculation of 4 yield-based valuation metrics
⚖ Historical average tracking for each yield
🎯 Visual scoring system:
🟥 0–1 = Weak
🟨 2 = Neutral
🟩 4 = Strong (all metrics above average)
🎛️ Toggle visibility of each yield independently
🧮 Fully compatible with other Greer Financial Toolkit indicators
🛠 Ideal For
Long-term value investors
Dividend and cash-flow-focused investors
Analysts seeking clean yield visualizations
Greer Toolkit users combining with Greer Value and BuyZone
Greer Value📈 Greer Value
This indicator evaluates the year-over-year (YoY) growth consistency of five key fundamental metrics for any stock:
Book Value Per Share
Free Cash Flow
Operating Margin
Total Revenue
Net Income
The script tracks whether each metric increases annually based on financial statement data (FY), then calculates both individual and aggregate increase percentages over time. A color-coded table is displayed on the most recent bar showing:
Raw counts of increases vs. checks per metric
Percentage of years with growth
Overall "Greer Value" score indicating total consistency across all five metrics
✅ Green = Strong YoY growth
❌ Red = Weak or inconsistent growth
Use this tool to help identify fundamentally improving companies with long-term value creation potential.
QoQ PAT, Sales & OPM% Labels by GauravThis indicator automatically displays the Quarter-over-Quarter (QoQ) percentage change in Sales, PAT (Profit After Tax), and Operating Profit Margin (OPM%) directly on the price chart.
It fetches quarterly financial data using TradingView’s request.financial() function for:
Sales (TOTAL_REVENUE),
PAT (NET_INCOME),
Operating Profit (OPER_INCOME).
For each earnings update, it calculates:
Sales QoQ %: Growth in sales vs. the previous quarter,
PAT QoQ %: Growth in PAT vs. the previous quarter,
OPM %: Operating Profit Margin = (Operating Profit / Sales) × 100.
This helps traders and investors quickly visualize fundamental growth trends right alongside the candlestick chart, improving fundamental + technical analysis integration.
S&P 500 Top 25 - EPS AnalysisEarnings Surprise Analysis Framework for S&P 500 Components: A Technical Implementation
The "S&P 500 Top 25 - EPS Analysis" indicator represents a sophisticated technical implementation designed to analyze earnings surprises among major market constituents. Earnings surprises, defined as the deviation between actual reported earnings per share (EPS) and analyst estimates, have been consistently documented as significant market-moving events with substantial implications for price discovery and asset valuation (Ball and Brown, 1968; Livnat and Mendenhall, 2006). This implementation provides a comprehensive framework for quantifying and visualizing these deviations across multiple timeframes.
The methodology employs a parameterized approach that allows for dynamic analysis of up to 25 top market capitalization components of the S&P 500 index. As noted by Bartov et al. (2002), large-cap stocks typically demonstrate different earnings response coefficients compared to their smaller counterparts, justifying the focus on market leaders.
The technical infrastructure leverages the TradingView Pine Script language (version 6) to construct a real-time analytical framework that processes both actual and estimated EPS data through the platform's request.earnings() function, consistent with approaches described by Pine (2022) in financial indicator development documentation.
At its core, the indicator calculates three primary metrics: actual EPS, estimated EPS, and earnings surprise (both absolute and percentage values). This calculation methodology aligns with standardized approaches in financial literature (Skinner and Sloan, 2002; Ke and Yu, 2006), where percentage surprise is computed as: (Actual EPS - Estimated EPS) / |Estimated EPS| × 100. The implementation rigorously handles potential division-by-zero scenarios and missing data points through conditional logic gates, ensuring robust performance across varying market conditions.
The visual representation system employs a multi-layered approach consistent with best practices in financial data visualization (Few, 2009; Tufte, 2001).
The indicator presents time-series plots of the four key metrics (actual EPS, estimated EPS, absolute surprise, and percentage surprise) with customizable color-coding that defaults to industry-standard conventions: green for actual figures, blue for estimates, red for absolute surprises, and orange for percentage deviations. As demonstrated by Padilla et al. (2018), appropriate color mapping significantly enhances the interpretability of financial data visualizations, particularly for identifying anomalies and trends.
The implementation includes an advanced background coloring system that highlights periods of significant earnings surprises (exceeding ±3%), a threshold identified by Kinney et al. (2002) as statistically significant for market reactions.
Additionally, the indicator features a dynamic information panel displaying current values, historical maximums and minimums, and sample counts, providing important context for statistical validity assessment.
From an architectural perspective, the implementation employs a modular design that separates data acquisition, processing, and visualization components. This separation of concerns facilitates maintenance and extensibility, aligning with software engineering best practices for financial applications (Johnson et al., 2020).
The indicator processes individual ticker data independently before aggregating results, mitigating potential issues with missing or irregular data reports.
Applications of this indicator extend beyond merely observational analysis. As demonstrated by Chan et al. (1996) and more recently by Chordia and Shivakumar (2006), earnings surprises can be successfully incorporated into systematic trading strategies. The indicator's ability to track surprise percentages across multiple companies simultaneously provides a foundation for sector-wide analysis and potentially improves portfolio management during earnings seasons, when market volatility typically increases (Patell and Wolfson, 1984).
References:
Ball, R., & Brown, P. (1968). An empirical evaluation of accounting income numbers. Journal of Accounting Research, 6(2), 159-178.
Bartov, E., Givoly, D., & Hayn, C. (2002). The rewards to meeting or beating earnings expectations. Journal of Accounting and Economics, 33(2), 173-204.
Bernard, V. L., & Thomas, J. K. (1989). Post-earnings-announcement drift: Delayed price response or risk premium? Journal of Accounting Research, 27, 1-36.
Chan, L. K., Jegadeesh, N., & Lakonishok, J. (1996). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Chordia, T., & Shivakumar, L. (2006). Earnings and price momentum. Journal of Financial Economics, 80(3), 627-656.
Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis. Analytics Press.
Gu, S., Kelly, B., & Xiu, D. (2020). Empirical asset pricing via machine learning. The Review of Financial Studies, 33(5), 2223-2273.
Johnson, J. A., Scharfstein, B. S., & Cook, R. G. (2020). Financial software development: Best practices and architectures. Wiley Finance.
Ke, B., & Yu, Y. (2006). The effect of issuing biased earnings forecasts on analysts' access to management and survival. Journal of Accounting Research, 44(5), 965-999.
Kinney, W., Burgstahler, D., & Martin, R. (2002). Earnings surprise "materiality" as measured by stock returns. Journal of Accounting Research, 40(5), 1297-1329.
Livnat, J., & Mendenhall, R. R. (2006). Comparing the post-earnings announcement drift for surprises calculated from analyst and time series forecasts. Journal of Accounting Research, 44(1), 177-205.
Padilla, L., Kay, M., & Hullman, J. (2018). Uncertainty visualization. Handbook of Human-Computer Interaction.
Patell, J. M., & Wolfson, M. A. (1984). The intraday speed of adjustment of stock prices to earnings and dividend announcements. Journal of Financial Economics, 13(2), 223-252.
Skinner, D. J., & Sloan, R. G. (2002). Earnings surprises, growth expectations, and stock returns or don't let an earnings torpedo sink your portfolio. Review of Accounting Studies, 7(2-3), 289-312.
Tufte, E. R. (2001). The visual display of quantitative information (Vol. 2). Graphics Press.
Stock metrics and valueThis indicator shows:
- the valuation metrics for a stock on a table on top right: PE, EPS, dividend, ROIC, ROE, ROA, EPS growth, FCF growth, Equity growth, revenue Growth
- the fair value and the value with 50% margin of safety as chart lines
The lines will be red when they are above the current price and red when they are below the current price.
The colors on the table will be red when the values are below 10% and green when they are above, that means when everything is green the metrics for the stock are good.
