spb/tools-spboucher-ai

1{2  "slug": "wrds",3  "name": "Wharton Research Data Services (WRDS)",4  "aliases": ["WRDS"],5  "vendor": { "name": "The Wharton School, University of Pennsylvania", "slug": "wharton", "website": "https://wrds-www.wharton.upenn.edu" },6  "homepage_url": "https://wrds-www.wharton.upenn.edu/",7  "docs_url": "https://wrds-www.wharton.upenn.edu/pages/about/",8  "repo_url": "https://github.com/wharton/wrds",9  "product_type": "platform",10  "product_status": "active",11  "summary": "Institution-subscribed research data platform from Wharton hosting CRSP, Compustat, TAQ, OptionMetrics and dozens of other vendors' databases with web queries, SQL, SAS, Python and R access",12  "description": "Wharton Research Data Services is the data platform operated by the Wharton School of the University of Pennsylvania that academic, government and commercial institutions subscribe to for access to licensed research databases. Its vendor list spans more than fifty providers, including CRSP, S&P Global Market Intelligence (Compustat and Capital IQ), NYSE Trade and Quote (TAQ), OptionMetrics, Audit Analytics, BoardEx, LSEG, FactSet, PitchBook, Preqin, RavenPack, CSMAR and the Fama-French factors, with some datasets such as TRACE, OTC Markets and Federal Judicial Center data included for all subscribers. WRDS normalizes the data into a PostgreSQL-backed warehouse with documentation, linking tables and classroom guides.\n\nUsers reach the data through web query forms, the WRDS Cloud via SSH and JupyterHub, SAS Studio, FTP and direct PostgreSQL connections; the official wrds Python package (BSD-3-Clause) wraps the connection with helpers to list libraries and tables and run SQL, and R connects through standard PostgreSQL drivers. Accounts are issued by subscribing institutions by role (faculty, PhD, research assistant, master's and undergraduate, staff, class accounts) with expiration dates and mandatory two-factor authentication; each institution's subscription determines which databases are visible.\n\nWRDS is the standard source for empirical finance and accounting papers because journals and referees expect CRSP/Compustat-based samples. Its constraints are institutional: individuals cannot subscribe, vendor licences prohibit redistribution and often restrict commercial use, downloads of very large tables (TAQ) must run on the WRDS Cloud, and availability of any specific database depends on the institution's contracts.",13  "capabilities": ["Hosted access to CRSP, Compustat, TAQ, OptionMetrics, Audit Analytics, BoardEx and other vendors", "Web query forms with variable selection and date filters", "WRDS Cloud: SSH, JupyterHub and SAS Studio", "Direct PostgreSQL access and the wrds Python package", "Linking tables and classroom guides", "Role-based accounts with two-factor authentication"],14  "workflows": ["Merging CRSP returns with Compustat fundamentals for an asset-pricing study", "Processing TAQ intraday data on the WRDS Cloud", "Class accounts for an empirical finance course"],15  "advantages": ["Canonical datasets expected by finance journals", "Multiple access paths including SQL and Python", "Documentation and linking tables maintained centrally"],16  "limitations": ["Institutional subscription only; no individual accounts", "Database availability varies by institution's contracts", "Vendor licences prohibit redistribution", "Large extracts must run on WRDS infrastructure"],17  "prerequisites": ["Account at a subscribing institution", "Two-factor authentication"],18  "audiences": ["Finance and accounting researchers", "PhD students", "Instructors of empirical finance courses"],19  "alternatives": ["databento", "firstrate-data", "sec-edgar", "bloomberg-terminal", "polygon-io"],20  "comparison_notes": "Databento, Massive and FirstRate Data sell market data to anyone but lack the accounting and ownership databases WRDS hosts; SEC EDGAR is the free primary source for filings that Compustat and Audit Analytics structure; the Bloomberg Terminal is a per-seat commercial alternative for recent data without WRDS's research-oriented historical panels.",21  "categories": [{ "slug": "market-data-apis", "primary": true }, { "slug": "hf-finance-research" }],22  "tags": ["market-data", "fundamentals", "sql", "academic", "python"],23  "use_cases": ["access-market-data", "analyze-intraday-data", "write-papers"],24  "operating_systems": ["web", "any"],25  "execution_modes": ["cloud"],26  "interfaces": ["web", "api", "sdk", "cli"],27  "deployment_models": ["saas"],28  "integrations": ["PostgreSQL", "Python (wrds package)", "R", "SAS", "JupyterHub", "Stata"],29  "data_formats": ["SQL tables", "CSV", "SAS datasets", "Stata .dta", "Parquet (export)"],30  "languages": ["SQL", "Python", "R", "SAS"],31  "source_model": "proprietary",32  "pricing_model": ["enterprise", "academic"],33  "self_hostable": false,34  "sources": [35    { "url": "https://wrds-www.wharton.upenn.edu/", "type": "official_site", "title": "Wharton Research Data Services", "supports": ["name", "summary"], "checked_at": "2026-11-02" },36    { "url": "https://wrds-www.wharton.upenn.edu/pages/about/", "type": "official_docs", "title": "About WRDS", "supports": ["description", "vendor"], "checked_at": "2026-11-02" },37    { "url": "https://wrds-www.wharton.upenn.edu/pages/about/wrds-account-types/", "type": "official_docs", "title": "WRDS Account Types", "supports": ["limitations", "prerequisites", "interfaces"], "checked_at": "2026-11-02" },38    { "url": "https://wrds-www.wharton.upenn.edu/pages/about/data-vendors/", "type": "official_docs", "title": "WRDS Data Vendors", "supports": ["capabilities"], "checked_at": "2026-11-02" },39    { "url": "https://pypi.org/project/wrds/", "type": "package_registry", "title": "wrds · PyPI", "supports": ["integrations", "repo_url"], "checked_at": "2026-11-02", "note": "Official Python client, BSD-3-Clause" }40  ],41  "confidence": "high",42  "uncertainty_note": "pricing_url omitted: subscriptions are negotiated per institution. Redistribution restrictions are stated per vendor licence rather than on a single public terms page.",43  "discovery_method": "editorial-research",44  "depth": "deep",45  "editorial_status": "reviewed",46  "visibility": "public",47  "featured": false,48  "author": "batch-E"49}50