Methodology
How we calculate
Two views of one company: its own financial discipline, and its position in the sector.
Two views
We read every ticker twice: how the company holds its own financial discipline, and how it looks against its sector.
The three layers combine, weighted, into a single composite score from 0 to 100: Quality 25% · Valuation 25% · Growth 20% · Outlook 15% · Health 15%. When the outlook is unavailable — a fresh IPO, thin analyst coverage — the method falls back to a four-axis balance, and the remaining weights rise in proportion. On the ticker page the composite score shows as a relative rank within the sector; the in-depth view adds an approximate range, and the quick view shows the numeric value. The reader draws the conclusion; the method only describes where the signals stand.
Worked example
The same layers on a live Apple snapshot — step by step, from single signals to the closing read.
AAPL · Apple Inc. · data as of 21 May 2026
Layer 1: 8 of 9 financial-discipline checks pass — a steady foundation.
What it does
The method describes financial discipline and sector context; it does not forecast the price or advise action.
Does
- Describes the company's financial discipline over recent cycles through standard accounting signals.
- Gives sector context through ranks against peers, instead of absolute numbers that are hard to read without knowing the industry.
- Documents its own limits openly — where data is thin and where a check does not apply.
Doesn't
- Does not forecast the price or imitate predictive research models.
- Does not account for management quality, competitive advantages, regulatory news, or geopolitics.
- Gives a rule-based classification (Buy candidate / Hold / Avoid) — a classification of fundamentals against the sector, not a price forecast and not investment advice. The rule's thresholds are sharp, with no smoothing: a value just under the line and one just over it fall into different classes, and we show that honestly rather than mask it with gradients.
- Does not guarantee returns: the classification timeline on the ticker page illustrates how the method read past quarters, not a validation of returns.
Limits
Where the method works less well, or not at all — we say so plainly instead of hiding it.
Academic basis
The original fundamental-quality logic was validated on deeply undervalued small- and mid-cap companies. Applying it to growth names and mega-caps sits outside the perimeter of those checks.
Signals from the past
The composite score rests on historical filings. The optional outlook layer adds a forward dimension, but none of its signals is a price prediction.
The financial sector
The classic valuation multiples and debt metrics work differently for banks, insurers, and brokers. The page flags when a ticker belongs to Financials or Real Estate.
Survivorship in the sector medians
Sector medians are computed from the current S&P 500 slice. Delisted or acquired companies do not re-enter the sample — a known limit on backward-looking comparisons.
One ticker is not statistics
The classification timeline shows how the method read a company in a few past quarters. It illustrates the logic; it is not a full validation — the data is limited and transaction costs are left out.
Partial data
When a provider is missing something, we show what can be computed and mark the missing values explicitly. No invented fill-ins.
Analyst optimism bias
When the outlook is on, some sub-signals come from analyst estimates, which the literature puts at roughly 5–15% too optimistic. That is why realized EPS growth from SEC filings serves as a separate cross-check sub-signal.
Sample for the outlook axis
Outlook percentile ranks need enough valid peers in the sector. For thin sectors the rank shows '—' even after a full data refresh.
Classification timeline without the outlook axis
The quarterly timeline is built on three dimensions: fundamental quality, valuation, and growth. The outlook dimension is absent from the archive — it would need analyst consensus for the past quarter, and we do not store retrospective estimates. That is an honest limit of the archive, not a bug.
Backtest check
We test the method with a backtest — whether it selects stocks with better future returns than the market. As of the last run, no statistically significant edge in selection showed up; in some runs the relationship was even negative. So the verdict stays a classification. We will add a claim about predictable returns only once a backtest shows a durable edge.
Glossary
The terms that show up in a brief, kept short and in plain words.
- P/E
- The share price divided by earnings per share over the trailing twelve months (TTM): the price paid for one dollar of yearly profit.
- FCF
- The cash a company keeps after running the business and paying for equipment and other long-term assets.
- capex
- Money spent to buy or improve long-lived assets such as plants, equipment, or property.
- EBITDA
- Earnings before interest, taxes, depreciation, and amortization: a rough proxy for operating profit before financing and accounting effects.
- EV
- Market capitalization plus net debt: the total price to buy the whole business, not just its shares.
- D/E
- Total debt divided by shareholder equity: how much the company borrows relative to the owners' capital.
- current ratio
- Current assets divided by current liabilities: whether short-term resources cover short-term bills.
- ROE
- Net income divided by shareholder equity: the profit earned on each dollar of the owners' capital.
- ROIC
- Operating profit divided by all invested capital (debt plus equity): how well the company turns its full funding base into profit.
- gross margin
- Gross profit as a share of revenue: what is left from each sales dollar after the direct cost of the goods sold.
- operating margin
- Operating profit as a share of revenue: what is left from each sales dollar after running costs, before interest and tax.
- dividend yield
- A year of dividends divided by the share price: the annual cash return at today's price.
- market cap
- The share price times the number of shares outstanding: the market's price tag on all of the equity.
- revenue growth YoY
- The percentage change in revenue against the same period one year earlier.
- net income
- What is left of revenue after every cost, including interest and tax: the bottom-line profit.
- F-Score
- A 0-to-9 score from nine pass/fail checks on profitability, leverage, and efficiency (Joseph Piotroski, 2000): a reading of past financial strength, not a forecast.
- Piotroski
- The accounting researcher who designed the F-Score (Joseph Piotroski, Stanford, 2000). Kept in the Latin spelling.
- sector median
- The middle value of a metric across companies in the same GICS sector: the yardstick for cheap or expensive within an industry.
- composite score
- A weighted blend of a company's percentile ranks across valuation, growth, quality, and health.
- value trap
- A stock that looks cheap on its multiples but carries weak fundamentals (a low F-Score), where the low price reflects a declining business rather than a bargain.
- fundamentals
- The core financial facts of a business (profitability, debt, efficiency, cash flow) drawn from its filings, as opposed to its share-price behavior.
Disclaimer
This is an analytical brief, not investment advice — any decision stays with you.
This is an automated analysis based on public financial data. It is a general, informational brief and does not account for your investment goals, financial situation, time horizon, or risk tolerance. The analysis is not investment advice and does not replace a personal consultation. It combines a company's historical filings with analyst-consensus signals, but it does not weigh management quality, competitive advantages, regulatory news, or geopolitical risk. The F-Score reflects past financial behavior, not a forecast of the future; consensus signals carry a documented optimistic bias and are used as a stress test. Any investment decision stays with you, and PlainTicker is not responsible for its outcome. If the amount is material to your finances, consult a licensed financial adviser first. The rule-based classification (Buy candidate / Hold / Avoid) is the output of the method's rule, not personal advice and not a price forecast; as of the last run, the backtest found no statistically significant edge in selection, and in some runs the relationship was negative.