How Stock Scores
Actually Work
No black boxes. No marketing fluff. See exactly how we score every stock.
The 3 Rules Behind Every Score
Fundamentals first. Industry context. Conservative by default.
Fundamentals Over Momentum
We ignore price momentum entirely. A stock going up doesn't make it better. A stock going down doesn't make it worse. We analyze the business, not the ticker.
Industry-First Context
A bank isn't a tech company. REITs aren't retailers. Each industry has metrics that matter, and metrics that don't. We score accordingly.
Conservative by Default
When in doubt, we penalize. We'd rather flag a potential issue than miss one. Our job is to surface concerns, not hide them.
The 7 Score Categories
7 equally weighted categories, led by the Valuation Model. Over 80 metrics analyzed per industry.
Valuation Model
Is this stock over or undervalued?
Algorithmically selects the most statistically reliable valuation multiples for each stock, then evaluates whether it appears over or undervalued relative to its own price history. Fast growers are valued on growth-adjusted ratios; slow growers shift to yield-based metrics.
Growth
Is it expanding?
Analyzes revenue, earnings, and cash flow growth over multiple time periods. Investors typically prefer companies that are growing, and we quantify how fast.
Profitability
Is it making money?
Gauges how effectively the company converts revenue into profit and generates returns for shareholders. High margins often indicate pricing power or operational efficiency.
Financial Health
Can it survive a downturn?
Stress-tests the balance sheet for red flags. High debt, poor liquidity, or weak interest coverage can signal trouble, especially when the economy turns.
Dividends
Is the payout safe?
Checks if the dividend is growing, well-covered by earnings, and sustainable long-term.
Management
Are they efficient?
Assesses capital allocation and shareholder dilution from stock-based compensation.
Analyst
What does Wall St. think?
Aggregates consensus ratings and price targets. Useful context, but no one knows the future.
No One-Size-Fits-All Templates
Metrics aren't universal. Our algorithm adapts to what actually matters.
| Industry | Key Metrics Used | Metrics Ignored | Why |
|---|---|---|---|
| Banks | Net interest margin, deposits growth, P/E | FCF, operating margins | Banks don't have traditional cash flows |
| REITs | FFO, P/FFO, dividend yield, occupancy | Earnings, P/E | GAAP earnings distorted by depreciation |
| Insurance | Combined ratio, book value, P/B | Traditional margins | Underwriting profit is the key metric |
| Tech / Software | Revenue growth, FCF margins, P/FCF | Dividend metrics (often N/A) | Growth and cash generation matter most |
| Consumer Retail | Same-store sales, inventory turnover, margins | None | Operational efficiency is key |
| Utilities | Dividend yield, payout ratio, rate base growth | High growth metrics | Regulated, stable businesses prioritize income |
This is a simplified view. The actual algorithm considers dozens of industry-specific adjustments.
Beyond Industry Templates
Deep precision. Individual tickers. Customization for every stock in our database.
Not all tech companies are the same. Meta and Amazon are both "tech," but they're valued completely differently. Our algorithm finds the most reliable valuation ratio for each stock, not based on industry, but on the stock's own historical data.
How the Valuation Selection Algorithm Works
Adapts to Volatility
We check how much each valuation ratio (P/E, P/FCF, etc.) has fluctuated historically. High volatility = less reliable signal.
Tests Predictiveness
Does the ratio tend to revert to its own average over time? Higher auto-correlation = more meaningful comparisons to historical values.
Filters Outliers
If a ratio frequently spikes to 200x then drops to 10x, it's not a stable measure. We penalize ratios with frequent extreme moves.
Growth-Aware Selection
Fast-growing companies are valued on growth-adjusted ratios like P/FCF-to-revenue-growth. Slower growers shift to yield-based metrics like risk premium.
Real Examples
Scores That Adapt
Dynamic updates throughout the trading day. Scores recalibrate as company fundamentals shift.
How Scores Get Calculated
Price Updates Throughout the Day
All scores update throughout the trading day. Price-sensitive metrics like valuation ratios and dividend yield reflect current prices in real time.
Earnings & Filings
Scores also update when companies report new financial data, earnings, or dividends.
Metric Recalibration
If a company's growth profile changes, the algorithm may select different valuation metrics.
Data Integrity
Clean data only. Audited filings. We handle the edge cases for you.
Point-in-Time Data
Historical scores use only data that was available at that moment. No look-ahead bias.
Restatement Handling
When companies correct old filings, we track both versions for accuracy and transparency.
Ticker Continuity
Mergers, renames, and spin-offs are tracked to maintain scoring continuity across corporate actions.
What We Don't Do
No Technical Analysis
We ignore price momentum. A stock going up doesn't make it better. A stock going down doesn't make it worse.
No Buy/Sell Signals
We grade the business, not the trade. Our scores tell you quality, not "when to buy."
No Black Boxes
Every penalty is visible. We show you exactly why a stock got the score it did.
No Rigid Templates
One size fits nothing. We never judge a bank with the same rules we use for a software company.
See It In Action
Search for any stock and see how it scores across all 7 categories.
Common Questions About Our Methodology
The details behind how Stock Scores are calculated
Why do you only use fundamentals and no technical analysis?
We believe a stock's quality should be measured by the business itself, not the ticker's recent price movement. Technical analysis and momentum-based scoring have a fundamental flaw: a stock going up scores higher simply because it's going up. That's the opposite of what a fundamental score should do. We analyze profitability, growth, financial health, valuation, and more. Not chart patterns. You can read more about why we built scores this way.
How do you handle different industries?
Every industry has different KPIs that matter. You wouldn't judge a bank's profitability the same way you'd judge a SaaS company's. We start with 20+ industry classifications, but we don't stop there. Many of our scores are customized at the individual stock level. The Valuation Model is the best example: it tests each valuation ratio for every stock individually, measuring how volatile it is, how predictive over time, whether it produces frequent outliers, and whether the company is a fast or slow grower. Then it selects only the ratios that produce trustworthy signals for that specific company. Banks get evaluated on net interest margin and efficiency ratios. REITs on FFO and occupancy. Two tech companies can get completely different metric selections based on their individual profiles.
What is per-stock metric selection?
This is the key innovation behind our Valuation Model. Even within the same industry, two companies can have very different valuation profiles. The algorithm tests each valuation ratio's reliability for a given stock: how volatile it is, how predictive it is over time, and whether it produces frequent outliers. It then selects only the ratios that produce trustworthy signals.
This is why META uses P/FCF while Amazon uses P/OCF and JPMorgan uses P/E. The algorithm finds what works for each company individually.
How do you avoid look-ahead bias in historical scores?
Every historical score is calculated using only data that was available at that exact point in time. If a company later restated their earnings, we use the original reported numbers for historical periods, not the corrected ones. This is called point-in-time accuracy, and it's essential for honest backtesting. Most platforms retroactively apply corrected data, which makes their historical analysis misleadingly accurate. See our Historical Stock Scores to explore up to 35 years of backtested data.
How many metrics do you analyze per stock?
Over 80 fundamental metrics across the 7 score categories. The exact metrics used vary by industry. A bank might be evaluated on 12 different metrics while a tech company might use a different set of 15. Each metric is weighted and scored against industry-specific benchmarks.
What happens when a company reports new financial data?
All scores update throughout the trading day. Price-sensitive metrics (including valuation ratios, dividend yield, and others) reflect current stock prices in real time. Other metrics update when companies report new financial data, earnings, or dividends.
Can I see exactly which metrics are used for a specific stock?
Yes. When you view any stock's scores on the platform, you can drill into each category to see the specific metrics being analyzed and how they contribute to the score. Full transparency is a core principle. No black boxes. Try it with NVIDIA to see what this looks like.
How many stocks do you score?
Over 100,000 stocks across 70+ global exchanges. The same methodology described on this page applies to every scored stock, with industry-specific and per-stock customization. With Historical Stock Scores, you can also see how approximately 40,000 of those stocks scored at any point over up to 35 years of history.
Are Stock Scores buy or sell recommendations?
No. Our scores are designed to give you a quick snapshot of a company's fundamental health across different areas. A stock with great scores isn't automatically a good investment, and a stock with some red flags isn't automatically bad. Use them to surface insights and inform your own research. You know your situation better than anyone.
Still have questions?