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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchCompustat is a commercial financial-data platform from S&P Global Market Intelligence. It turns company disclosures and related market information into structured datasets that researchers, investors, and financial-technology systems can use to compare companies, build screens, test investment signals, and analyze risk. Its value is not just the number of fields: it is the combination of standardized fundamentals, historical records, identifiers, and product options. The right way to use it depends on which Compustat dataset you have, what date its figures represent, and whether you need company or security data.
What is Compustat?
Compustat is a family of commercial datasets, not a single spreadsheet or uniform file. S&P Global Market Intelligence describes Compustat Financials as covering more than 80,000 active and inactive publicly traded companies worldwide, with North American history extending as far back as 1950 and North American point-in-time changes beginning in 1987. Those are product-level descriptions, not guarantees that every company or field has data for every year. Coverage depends on geography, product, field, and delivery channel. S&P Global’s Compustat Financials overview also lists more than 3,000 standardized financial items.
In practice, “Compustat” may mean North American or Global fundamentals, securities or market data, point-in-time snapshots, or a combined research product such as the CRSP/Compustat Merged Database (CCM). WRDS describes its Compustat North America fundamentals as including more than 500 company-level items across income statements, balance sheets, and flow-of-funds data. The differing field counts reflect product scope and descriptions, not a single universal count for every Compustat file. WRDS’s introduction to Compustat outlines the fundamentals collection.
Compustat’s purpose is to make company information easier to analyze consistently across firms and over time. S&P says its data draws on publicly available documents, company filings, annual reports, press releases, and local feeds. Analysts review disclosures and map items into a common structure; that work can involve judgment, so a standardized Compustat value is not necessarily a mechanical copy of a filing line.
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What data does Compustat contain?
Available content depends on the licensed product and geography. The main data families include:
| Data family | What it can include | Why it matters |
|---|---|---|
| Financial statements | Income-statement, balance-sheet, and cash-flow or flow-of-funds items, with annual, quarterly, year-to-date, or semiannual observations depending on the product. | Supports company comparisons, historical operating analysis, and financial-model inputs. |
| Supplemental fundamentals | Per-share items, debt, leases, pensions, taxes, working capital, employee counts, operating metrics, and industry-specific fields where available. | Adds detail for sector analysis, capital-structure work, and tailored screens. |
| Segments and ratios | Business or geographic segment information and research-oriented calculated ratios where offered. | Helps analyze business mix and derive measures without treating every issuer as identical. |
| Securities and market information | Security prices, dividends, splits, trading or listing history, and related corporate-action information, depending on the dataset. | Connects company fundamentals to securities and market activity. |
| Identifiers and classifications | Company and issue identifiers, historical identifiers, and industry classifications. | Enables more reliable entity matching than ticker-only joins. |
| Historical or point-in-time data | Snapshots or records that represent data at particular historical dates, depending on product and coverage. | Can help reconstruct what information was available for a historical analysis. |
S&P’s commercial description includes daily and monthly market data, pricing, dividends, splits, corporate-action history, and security-identifier history, as well as point-in-time snapshots. The exact fields and history must be checked for the particular license. S&P’s product description lists delivery and content options.
Identifiers: company is not the same as security
Compustat’s GVKEY is a permanent company identifier; IID identifies an issue or security within Compustat. CUSIP/CINS, ISIN, SEDOL, ticker, CIK, and industry codes may also appear, depending on product. In CRSP-linked work, PERMNO and PERMCO identify securities and companies in CRSP’s system. These identifiers answer different questions: one company can have multiple securities or listings, and identifiers can change through corporate events. The CRSP/Compustat guide describes GVKEY, IID, historical identifiers, and the organization of company and security records. Read the CRSP/Compustat Merged Database guide.
A ticker is a label, not a dependable permanent key. It can change, be reused, or represent only one of several securities associated with a company. Define whether your observation is a company, a security, or a company-period before choosing identifiers or joining datasets.
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What does “standardized” mean?
Standardization maps different companies’ reported information into common financial concepts. It can normalize variations in presentation and improve cross-company analysis, while retaining notes or data codes where an item needs context. S&P’s materials describe analyst review of statements, management discussion, footnotes, and other disclosures, with data generally aligned to U.S. GAAP and IFRS. Some metrics may be non-GAAP or calculated rather than directly reported. The WRDS/S&P presentation on Compustat discusses analyst judgment, notes, and data codes.
Standardization improves usability; it does not erase accounting or business differences. Fiscal calendars, acquisitions, discontinued operations, leases, stock compensation, foreign exchange, accounting frameworks, and industry reporting can all affect comparability. For detailed work, consult the data dictionary and notes, then validate material values against original disclosures.
| Data approach | Best suited to | Main caution |
|---|---|---|
| Standardized fundamentals | Cross-company analysis and long-run research. | Mappings can involve analyst judgment and may not preserve every filing detail in the numeric field. |
| As-reported or unrestated data, where available | Examining figures closer to their original presentation. | Comparability and cleanup may be harder; confirm the exact product’s definition. |
| Point-in-time data | Historical analysis that needs to account for when data entered the information set. | It helps address look-ahead bias but still requires correct release-date and revision logic. |
| Current or restated historical data | Consistent analysis using the latest available historical series. | Later revisions may include information unavailable at the historical decision date. |
| Raw filings and XBRL | Source-level review, custom extraction, and auditability. | Taxonomy changes, company-specific extensions, and inconsistent presentation demand engineering and validation. |
Compustat North America and Compustat Global are different workflows
North American and Global data should not be treated as interchangeable editions of the same table. Their field availability, definitions, history, currencies, accounting contexts, and identifier behavior can differ. WRDS groups Compustat Global into fundamentals, index constituents and index prices, and securities data. WRDS’s overview of Compustat Global describes these broad components.
| Dimension | North America | Global |
|---|---|---|
| Geographic scope | U.S. and Canadian companies. WRDS describes more than 50,000 active and inactive publicly held companies in its annual-update demonstration. | Companies outside the North American collection; coverage and fields depend on country and product. |
| History | S&P states North American history reaches as far back as 1950; point-in-time changes are described from 1987. | History varies by company, country, field, and dataset; do not assume North American start dates apply. |
| Accounting context | U.S. and Canadian reporting contexts still require attention to company and industry differences. | Local reporting practices, IFRS, local GAAP, and currency treatment add analysis and validation needs. |
| Common complication | Fiscal-year changes, delistings, and multiple securities can affect a historical sample. | Those issues remain, with additional country, currency, calendar, and identifier complexity. |
The North American company count above comes from a WRDS annual-update demonstration, while the broader global count and historical descriptions come from S&P’s product page. WRDS’s North America annual-update demonstration provides its stated coverage context.
How financial technology uses Compustat
Quantitative investing and backtesting
Researchers and investment systems can calculate signals such as book-to-market, earnings-to-price, return on assets, profitability, asset growth, leverage, cash-flow yield, and sales growth. Those measures can feed factor research, portfolio rankings, and security selection. A backtest is only credible if the inputs reflect the information that could have been known at the time, and if the sample handles delisted firms, revisions, and the mapping from company accounts to traded securities.
Screening, valuation, and financial modeling
Fintech products can use fundamentals to filter companies by revenue, margins, debt, cash, capital spending, dividends, or share-count changes. Analysts can use historical statements for comparable-company work, operating benchmarks, capital-structure analysis, and scenario models. Compustat provides structured inputs; it does not decide which peer group, accounting adjustment, or forecast assumption is appropriate.
Credit and risk analytics
Leverage, liquidity, and interest-coverage measures can support issuer monitoring, sector stress tests, or credit research. Compustat alone is not a complete credit-risk system: a model may also need bond prices, ratings, spreads, loan information, legal events, macroeconomic variables, and robust issuer matching.
Machine learning and data infrastructure
Structured fundamentals can serve as features for earnings forecasts, bankruptcy research, anomaly detection, and industry benchmarking. Teams should test for missingness patterns, changing definitions, restatements, entity changes, and leakage from information recorded after the prediction date. Commercial delivery options listed by S&P include APIs, cloud, desktop, feeds, marketplace extracts, Capital IQ, Workbench, Snowflake, Databricks Delta Sharing, and Xpressfeed; availability and terms depend on the product and contract. S&P lists Compustat delivery options.
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Compustat, CRSP, and CCM: fundamentals versus market history
Compustat is chiefly used for company fundamentals and related identifiers, with some products also covering market and corporate-action information. CRSP is chiefly associated with historical security prices, returns, distributions, delisting information, and permanent market identifiers. CRSP describes PERMNO as a permanent identifier for tracking U.S.-listed equities through corporate restructurings. CRSP’s research data overview provides context on its products and identifiers.
The CRSP/Compustat Merged Database links CRSP security-level data with Compustat company-level fundamentals through historical relationships. The link is time-dependent: a company can have multiple securities, and relationships can change. The merge is not simply a ticker lookup. CRSP describes the merged database as mapping complex relationships between the two systems. CRSP’s overview of its data products explains the merged database.
When combining the sources, use the appropriate CCM historical link records, respect their effective dates and link attributes, and choose the company or security level required by the analysis. Avoid joining on a current ticker or current CUSIP alone.
How to access Compustat
| Route | Typical fit | What to verify |
|---|---|---|
| WRDS | University and institutional research using query and extraction tools. | Whether the institution has the required Compustat and any CRSP/CCM licenses; permitted uses and available tables. |
| S&P Global commercial products | Organizations building research, investment, or production data systems. | Fields, geography, delivery, latency, user scope, redistribution rights, and contract terms. |
| Academic Research Essentials | Education and research settings seeking a specific academic package. | Included company universe, fields, securities pricing, and restrictions; it is not the full commercial universe. |
| APIs, feeds, or cloud delivery | Engineering teams integrating licensed data into a warehouse or application. | Schema, update cadence, historical revisions, support, and production or customer-facing rights. |
WRDS is a research platform and access route, not the owner of Compustat. A WRDS subscription does not automatically include every third-party dataset: vendor licenses may be separate. WRDS also directs prospective subscribers to contact it about pricing. WRDS explains its subscriptions and data access. Its query tools support outputs including text, CSV, Excel, HTML, SAS, Stata, dBase, and SPSS. WRDS platform information describes available output formats.
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S&P’s Academic Research Essentials is a particular academic package, not the entire commercial Compustat universe. Its product page describes Compustat fundamentals for more than 12,000 companies plus securities pricing data. See S&P Global Academic Research Essentials.
Commercial pricing is generally quote-based rather than publicly listed. A buyer should confirm costs, license scope, and redistribution rights directly; technical access does not itself authorize serving data to customers or using it in a commercial product.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A responsible Compustat workflow
- Define the observation. Decide whether the analysis is at company, security, fiscal-period, company-quarter, company-year, or company-security-period level.
- Select the scope. Choose North America or Global, relevant frequency, fundamentals or securities, and current, unrestated, or point-in-time data as required.
- Read the data dictionary. Confirm field definitions, units, signs, currency, frequency, fiscal-period meaning, missing-value codes, notes, and whether an item is reported, standardized, or calculated.
- Set date logic. Keep fiscal period-end separate from the date information became available. Use filing or availability dates and revision history where supplied; if exact availability is unavailable, document a conservative lag policy.
- Interpret missing values. Determine whether a blank or code means unreported, inapplicable, combined, insignificant, unavailable, or not yet collected. Never silently turn every missing value into zero.
- Validate key fields. For high-stakes work, compare a sample of important observations with annual reports, quarterly reports, or filings, and record how discrepancies are handled.
- Link market data historically. For CRSP combinations, use CCM relationship records and effective dates; account for multiple securities and delisted issues when the design requires them.
- Preserve reproducibility. Record dataset and table, extraction date, fields, filters, version or delivery details, currency treatment, missing-value rules, outlier handling, and point-in-time or restatement choices.
For example, a historical value screen could use annual fundamentals, apply an information-availability rule, link each eligible company to securities using historical CCM relationships, retain delisted securities where appropriate, and document the data vintage. This describes the logic, not a guaranteed menu path or field name; consult the data dictionary for the licensed interface.
Common mistakes and how to avoid them
- Joining on ticker: Tickers change and do not represent a permanent company-security relationship. Use the identifiers and historical links suited to the source.
- Using today’s revised values in a historical test: Later restatements can introduce future information. Use point-in-time or unrestated data where available, or document an availability lag and its limitations.
- Replacing missing values with zero: Missingness can encode materially different situations. Consult data codes and notes.
- Assuming standardized means identical accounting: Standardized fields still need interpretation across industries, accounting regimes, and corporate events.
- Dropping inactive firms: Excluding failed, acquired, or delisted companies can create survivorship bias in historical research.
- Mixing fiscal and calendar periods: Explicitly align period-end and information-availability dates with market or macroeconomic observations.
- Confusing company with security: One issuer may have multiple share classes, listings, or identifiers. Set the unit of analysis before extracting or linking records.
- Assuming WRDS access equals commercial rights: Confirm the actual vendor license and permitted uses, especially for customer-facing products or data redistribution.
Alternatives: when another source may fit better
| Alternative | May fit better when | Trade-off |
|---|---|---|
| CRSP | The core need is historical U.S. security prices, returns, distributions, delisting information, or permanent market identifiers. | It is not a substitute for broad global company fundamentals. |
| FactSet Fundamentals | An institution wants global fundamentals integrated into broader market-intelligence and investment workflows. | Coverage and depth depend on subscription; compare field definitions, history, identifiers, and delivery. |
| S&P Capital IQ or S&P Fundamental Data | Users need financial statements alongside company research, capital structure, transactions, estimates, or workflow tools. | May exceed the needs of a narrow historical research project; licensing and delivery terms matter. |
| Raw regulatory filings and XBRL | Source-level auditability, custom extraction, or low-cost access is the priority. | Requires substantial work on taxonomy changes, company-specific extensions, normalization, and entity resolution. |
| Public market-data APIs | A prototype, classroom project, dashboard, or exploratory analysis needs limited data. | Do not assume institutional history, inactive-company coverage, point-in-time revisions, or redistribution rights without checking them. |
WRDS lists FactSet as a separate vendor offering; availability and depth depend on subscription. WRDS’s FactSet listing provides access context. S&P describes its broader fundamental-data products for commercial users. Explore S&P Global fundamental data.
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Is Compustat the right choice?
- Academic researcher: It can be valuable for standardized historical fundamentals, especially when institutional WRDS access is available. Confirm the specific vendor subscriptions and whether the research needs CRSP/CCM.
- Quantitative investment team: Evaluate point-in-time support, historical identifiers, inactive-company coverage, delivery, and revision handling against the strategy’s backtesting needs.
- Fintech startup: Resolve commercial licensing and customer-facing redistribution before building around the data. Compare production delivery and rights as carefully as field coverage.
- Student or hobbyist: Check university access first; a commercial subscription may be excessive for a limited project.
- Data engineer focused on source fidelity: Raw filings may offer greater control, while Compustat can provide a normalized baseline. Some systems use both, validating structured values against original disclosures.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
