Structured stock research. Bear case first.
Versioned, archetype-calibrated research with one house fair value, a published low / high range, and visible source dates.
Every stock we research
Filter by rating, sector, and archetype. Sort by upside, analysis date, or alphabetically.
Coverage questions
Do you cover small caps and foreign listings?
Coverage expands by user request when a company has enough liquidity, audited disclosure, and data availability for the full methodology.
Questions, answered.
How is this different from traditional research?
The difference is consistency and independence. We apply the same versioned research framework across coverage, avoid banking or paid-rating conflicts, and publish the assumptions readers need without exposing proprietary implementation details.How often are reports updated?
The research program is organized around monthly publication cycles, but a ticker is not promised an update on a specific date. Use the report's analyzed/as-of dates and the current coverage hub to judge freshness; stale or unavailable data should not be treated as current.How accurate are the fair-value estimates?
Fair valueFair valueOur composite estimate of intrinsic per-share value, blended across DCF, exit-multiple, and reverse-DCF methods. Reported as a low/mid/high range to capture model uncertainty. is an evidence-backed range, not a promise. We triangulate through multiple valuation lenses and show risks, sensitivitySensitivity analysisA 5×5 grid showing how fair value moves under different combinations of two key drivers (typically Ke and terminal growth). Stress-tests the central case., assumptions, and source dates so readers can see what drives the conclusion.Is there a free tier?
Yes. Free accounts can read current featured research, build a watchlist, save reader notes, and use the in-app inbox. Individual adds historical archive access, saved workbooks, and configurable research updates. Professional adds PDF/DOCX export and developer access where those capabilities are available.Are humans involved?
The report lifecycle has no human approval gate. LLM roles generate each report, challenge its reasoning, and validate its methodology, data, and conclusions. Publication follows automatically only after deterministic structural, arithmetic, provenance, and public-boundary checks pass. No human review, approval, or sign-off is required. We do not publish internal prompts, routing, or calibration controls.Is StockMarketAgent.ai a registered investment adviser?
No. We publish educational research. We are not a broker-dealer, registered investment adviser, or fiduciary. Nothing on this site is personalized investment advice. See the Terms of Service §6 for the full responsibility-and-due-diligence clause.Where does your data come from?
Reports use dated inputs from configured providers and may include regulatory filings, company releases, standardized financial data, market data, and macro series. Each report should disclose key source dates; provider availability and licensing remain deployment-specific.How do you handle currency and jurisdiction?
Currency and listing context come from the dated source data for each security. Global-directory and search results show the exchange and use the recorded price currency; report assumptions should be checked before comparing cross-listed securities.
How we publish
We do not sell issuer-paid ratings or pre-clear conclusions. Reports expose key source dates and assumptions; confirmed corrections belong in the public log.
Editorial guidelines
The sourcing, publication-gate, disclosure, and correction standards that govern research eligibility.
Read moreCorrections policy
Confirmed factual corrections are recorded in a dated public log with the affected content and resolution.
Read moreAbout
Research platform publishing a free current featured report and versioned monthly-cycle equity coverage without a paid-rating product.
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