How the Q·Score works
A transparent, sector-normalised model that distils five fundamental dimensions into a single 0–10 rating. No black boxes.
What is Q·Score?
Q·Score is Quantify's proprietary rating model designed to give retail investors a fast, structured way to assess a stock's fundamental profile. Instead of requiring hours of financial statement analysis, Q·Score synthesises publicly available data into a single score from 0 to 10 — updated automatically on every page load.
The model was built around one core idea: quality of fundamentals should be judged relative to the sector, not on an absolute basis.A bank with a high debt-to-equity ratio is not in trouble — that's normal for banks. A utility growing revenue at 5% isn't failing — that's typical for utilities. Scoring everything by the same ruler produces misleading results. Q·Score adjusts every threshold by sector.
The score is intentionally not a buy or sell signal. It describes what the data says about a company's current fundamental state — nothing more.
The Formula
Five dimensions, each scored 0–10, combined with fixed weights:
The Five Dimensions
Measures business quality through profitability and capital efficiency.
How much of each revenue dollar becomes profit
How efficiently management uses shareholder capital
Real cash generated relative to market value
A high-quality business can weather downturns, fund growth internally, and compound returns over time. It's the foundation of any durable investment thesis.
Evaluates balance sheet strength and financial resilience.
Leverage relative to shareholder equity
Ability to cover short-term obligations
Fraction of quarters where actual EPS ≥ estimates
Financial stress often precedes equity destruction. A healthy balance sheet gives companies the flexibility to invest through cycles and avoid dilutive financing.
Captures momentum in revenues, earnings, and earnings surprise.
Year-over-year top-line expansion
Year-over-year bottom-line expansion
Beat rate and average magnitude of EPS beats
Revenue and earnings growth determine long-term value creation. Surprise quality captures whether management consistently under-promises and over-delivers.
Assesses how the stock is priced relative to fundamentals and analyst targets.
Gap between current price and consensus analyst target
Earnings multiple relative to sector norms
Where the stock sits in its annual trading range
Even great businesses can be poor investments if purchased at excessive prices. Valuation anchors the score to market reality, not just business quality.
Aggregates the collective view of professional equity analysts.
Share of analysts with a bullish rating
Score weighted by rating strength (strong vs. moderate)
More analysts = more reliable consensus signal
Sell-side analysts collectively process enormous amounts of proprietary data. Their consensus, while imperfect, is a useful independent signal to blend with fundamental metrics.
Sector Normalisation
Every metric threshold in Q·Score is looked up from a sector-specific table rather than applied universally. For example:
This means comparing a Q·Score of 7.5 for a bank and 7.5 for a SaaS company is fair — both are strong relative to their own sector's norms. Without normalisation, every bank would look over-leveraged and every utility would look like it's stagnating.
Rating Scale
Data Sources & Refresh
All underlying data — financial statements, analyst estimates, price data, and consensus targets — is sourced from Yahoo Finance. Q·Score is computed fresh on every page load using the latest available data, so the score can change daily as market conditions and company fundamentals evolve.
Analyst consensus ratings (the number of analysts with positive, neutral, or negative ratings) are aggregated by Yahoo Finance from multiple sell-side research providers. Quantify does not produce its own analyst ratings — it aggregates and displays third-party data.
Limitations
Q·Score is a quantitative model based on historical and current reported data. It has inherent limitations that any user should be aware of:
- Backward-looking data. Financial statements reflect the past. A company's fundamentals can deteriorate rapidly after reporting — Q·Score will not capture this until new data is published.
- No qualitative factors. Management quality, competitive moats, regulatory risk, and geopolitical exposure are not reflected in the score.
- Analyst consensus is lagging. Analyst price targets and ratings are updated infrequently and may not reflect the latest developments.
- Coverage gaps. Very small or thinly-covered stocks may have incomplete data, which can distort sub-scores. Q·Score defaults to neutral (5/10) for missing data points.
- Not a timing tool. A high Q·Score does not indicate when to enter or exit a position. Valuation and market timing require separate analysis.
Quantify.biz and the Q·Score are for informational and educational purposes only. Nothing on this site constitutes financial advice, investment advice, or a recommendation to buy or sell any security. Q·Score is a data aggregation and scoring tool — it describes what publicly available data shows about a company's fundamental profile. It is not a prediction of future performance.
Always consult a qualified financial advisor before making investment decisions. Past fundamentals do not guarantee future results.