Wrds Compustat Best Review

Note : Market equity (ME) is best obtained from CRSP monthly file ( mktcap or PRC * SHROUT ), then linked via CCM. 4.1 Web Query Interface WRDS web query is suitable for small extracts. Choose Compustat - Annual Updates , select GVKEY, DATADATE, AT, LT, SALE, and filter indfmt=‘INDL’ and consol=‘C’ (consolidated) and popsrc=‘D’ (domestic US). 4.2 SAS (most common legacy method) libname comp ‘/wrds/comp/sasdata/’; data annual; set comp.funda; where indfmt eq ‘INDL’ and consol eq ‘C’ and popsrc eq ‘D’; keep gvkey datadate fyr at lt ceq sale; if at > 0; run; 4.3 Python (recommended for modern workflows) import wrds import pandas as pd db = wrds.Connection() db.create_pgpass_file()

: WRDS, Compustat, empirical finance, data management, SAS, Python, Fama-French factors 1. Introduction Empirical research in finance and accounting relies heavily on standardized, historical financial statement data. Compustat (originally from Standard & Poor’s, now part of S&P Global Market Intelligence) provides over 50 years of annual and quarterly fundamentals for publicly traded companies. The Wharton Research Data Services (WRDS) platform acts as a unified delivery system, offering seamless access to Compustat alongside CRSP, OptionMetrics, IBES, and others. This paper serves both as a tutorial and a methodological reference for researchers who need to extract, clean, and merge WRDS Compustat data. wrds compustat

| Mnemonic | Description | Typical transformation | |----------|-------------|------------------------| | AT | Total assets | Book equity component | | LT | Total liabilities | For leverage | | CEQ | Common/ordinary equity | Book equity | | SALE | Net sales/turnover | Size proxy | | NI | Net income | Profitability | | EPSPX | Basic EPS (excl. extraordinary items) | Valuation ratios | | CSHO | Common shares outstanding | Market cap | | PRCC_F | Price close (fiscal year end) | For market-to-book | Note : Market equity (ME) is best obtained

Abstract Wharton Research Data Services (WRDS) Compustat is a cornerstone database for empirical research in corporate finance, accounting, and asset pricing. This paper provides a comprehensive guide to using WRDS Compustat, covering its data architecture (annual, quarterly, monthly, and daily files), key data items (e.g., AT – total assets, SALE – sales, NI – net income), and linkage to other databases (CRSP, IBES, Eventus). We detail access methods including web query, SAS, Python (via wrds package), and R. Common pitfalls—such as look-ahead bias, survivorship bias, improper handling of missing values, and adjusting for stock splits and dividends—are discussed with replicable code examples. Finally, we present a step-by-step empirical replication of a classic Fama–French (1993) factor construction using Compustat and CRSP data, demonstrating the workflow from raw data extraction to final regression analysis. The Wharton Research Data Services (WRDS) platform acts

Each file includes a unique gvkey (Global Company Key) as the permanent identifier. Annual files have datadate (fiscal year end date) and fyr (fiscal year month). Essential Compustat data items (annual):