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Company

LSEG aggregates a company “snapshot” with legal and trading identifiers (name variants, ISIN, ticker, LEI), exchange listings, sector/industry classifications, key executives, business description, and high‑level market metrics such as free‑float, market cap, and key price ratios. Company section of LSEG provides the following data:

  • Estimates — LSEG’s estimates data (largely from its I/B/E/S heritage) contain broker and consensus forecasts for EPS, revenue, EBITDA, cash flow, dividends, and target prices at multiple horizons, including detailed history of revisions, surprises versus actuals, and per‑analyst contributions.
  • Financials — For each company, LSEG provides standardized annual and interim financial statements, income statement, balance sheet, cash‑flow statement, with restated and as‑reported figures, per‑share data, and a broad set of computed ratios, all mapped to global accounting standards to enable cross‑country comparability.
  • Valuation — Valuation data combine market prices with fundamentals and estimates to produce metrics such as P/E, forward P/E, EV/EBITDA, EV/Sales, dividend yield, price‑to‑book, price‑to‑cash‑flow, and implied growth or cost‑of‑equity measures, usually across multiple time horizons and peer percentiles.
  • Relative Valuation — This layer adds peer‑group comparisons: for a chosen company, LSEG computes valuation multiples relative to a defined peer set (sector, region, custom list), providing distribution statistics (median, quartiles, z‑scores) and sometimes regression‑based fair‑value estimates.
  • ESG — LSEG’s ESG dataset assigns overall and pillar scores (environmental, social, governance), plus 100+ granular indicators such as emissions intensity, board structure, diversity, human‑capital policies, and controversies, along with historical trajectories and disclosure flags.
  • Segments — Segment data break company revenue, operating profit, assets, or other metrics down by business segment and geographic region, showing the contribution and margins of each segment, and often including historical restatements when companies change their segment reporting.
  • Peer Analysis — Using classifications and custom filters, LSEG constructs peer universes (by industry, size, region, factors) and provides side‑by‑side comparisons of price performance, valuation ratios, profitability, leverage, growth, and ESG metrics, with tools to rank and screen within the peer set.
  • Price History — LSEG maintains long‑run historical price and return time‑series for each listed share and related instruments (local and base‑currency prices, total returns, volume, high/low, corporate‑action adjustments), including support for multiple share lines and delisted names.
  • Significant Developments — This captures event‑level textual and structured data on corporate news: earnings announcements, guidance changes, M&A and restructuring, management changes, capital actions, regulatory issues, major contracts, and other market‑moving items, tagged by date, type, and entity.
  • Debt Structure — LSEG’s reference data link a company to its outstanding debt securities and credit facilities, detailing instruments’ coupons, maturities, seniority, covenants, embedded options, currencies, and issuance amounts, plus aggregate leverage metrics like net debt and maturity profiles.
  • CDS — For entities with traded credit derivatives, LSEG provides CDS quotes and time‑series (spreads, upfront points, curves by tenor), recovery and notional information, and sometimes derived measures such as implied default probabilities, all mapped to the issuing entity and sector.
  • Ownership Summary — Ownership data summarize the shareholder base, major institutions and insiders, percentage holdings, changes over time, free float, and investor type breakdowns (e.g., mutual funds, pension funds, hedge funds, strategic holdings), with underlying position‑level history where available.
  • Company Tree — LSEG maintains legal‑entity hierarchies and corporate‑structure data, showing parent‑subsidiary relationships, intermediate holding companies, cross‑holdings, and ultimate parents, often with regional and sector classifications for each node in the tree.
  • Value Chains — Value‑chain data aim to map a firm’s upstream suppliers and downstream customers, sectoral linkages, and sometimes revenue exposure to specific industries or themes, enabling supply‑chain risk analysis and thematic mapping around a focal company.