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How QTick computes its numbers

QTick puts 51 metrics on a stock dossier. Each one names the real method, then translates it — what it tells you, how it is calculated, and where it breaks down. No metric is a buy or sell trigger. This page collects the methods behind all of them, grouped the way a careful person actually reads a company.

The order is the product

A first-time investor sees forty numbers and does not know which matter. New buyers fixate on the price target. We deliberately flip that order: the questions that protect your money come first. This is a research order — what to check before committing capital, and why each ranks where it does. It is never a buy trigger.

  1. Can it survive?Before any other number: can this company go to zero? A great story on a balance sheet that cannot service its debt is a trap.
  2. Is the reporting honest?Everything else is built on the company's filings. If those are manipulated, the rest of the page is fiction.
  3. What's the worst case if you're wrong?You will be wrong sometimes. The downside sets your position size — upside only means something measured against it.
  4. Is it a good business?Durable businesses recover from mistakes; weak ones get punished for them. Margins, returns on capital, cash generation.
  5. Is the price sane?The best company in the world is a poor position at the wrong price. Valuation, never in isolation from quality.
  6. What's the setup and timing?Context for entry — not a trigger. The most overrated layer for a long-term holder, never the first thing to check.
  7. Who else is positioned, and what's coming?Divergence from the crowd is where edge lives — and an earnings date next week changes the whole risk picture.

survive → honest → downside → quality → price → timing → crowd

Every metric, by category

Credit & distressA falling DTD (especially below 2) tightens the case that structural stress is building — set it next to the accounting gauges (Altman Z, forensic flags) to triangulate.Covers 3 metricsRisk & tailsBeta tells you how much of a stock's price noise comes from broad market swings versus company-specific events.Covers 8 metricsOptions & dealer positioningA high implied move tells you the options market is paying up for protection or leverage into the nearest expiry — common ahead of earnings, a regulatory date, or a macro print, or when a name is in play.Covers 5 metricsTrend & technicalsRSI-14 tells you how stretched the tape is, not whether the fundamentals changed.Covers 11 metricsOur signal & track recordA positive net adds corroborating structure to a bullish thesis: several independent data streams point the same direction, not just one.Covers 4 metricsOdds & the avoid spineThe split bar tells you whether similar names — same red-flag count — historically closed higher or lower 12 months out.Covers 4 metricsOwnership & flowA high score tells you that multiple insiders — people with line-of-sight to the business — put their own cash in simultaneously and recently.Covers 3 metricsShare supply & dilutionA rising count means the company pays for things by creating new shares — each share you hold owns a shrinking slice of the business.Covers 5 metricsEarnings personalityStrengthens a pre-earnings thesis when pBeatNext sits above the pooled base rate and cohort_multiple (cell rate / pooled rate, populated only on the persistent-skill path) is meaningfully above 1.0; weakens it when pBeatNext sits below the pooled rate.Covers 2 metricsValuation & qualityA low PEG tightens the valuation case — you're paying less P/E per unit of growth, which is the core of a growth-at-a-reasonable-price argument.Covers 4 metricsFair Value / DCFA large gap to the price is a prompt to ask *why* — cheap for a reason, or genuinely mispriced? It's an input to your own view, never a trigger; the spread between the three methods shows how shaky the estimate is.Covers 1 metricForensicA low score forces you to discount the bull case: the financials themselves may not be trustworthy, so thesis strength depends on which test failed.Covers 1 metric

QTick shows cited data and code-computed models for self-directed research. Nothing here is a recommendation, solicitation, or investment advice. Where a metric’s live data pipeline is under review, its method is described but its current value is withheld rather than shown as reliable.