Center for Research in Security Prices (CRSP)

Center for Research in Security Prices (CRSP)
Name	Center for Research in Security Prices
Founded	1960
Location	University of Chicago, Chicago, Illinois
Focus	Historical financial market data, securities pricing

Contents

Center for Research in Security Prices (CRSP) The Center for Research in Security Prices (CRSP) is a research center based at the University of Chicago that maintains historical databases of securities prices and related identifiers. Founded to support empirical work by faculty and students, the center underpins research in finance, University of Chicago Booth School of Business, National Bureau of Economic Research, and a wide range of academic and industry projects. CRSP datasets are used by scholars involved with journals such as the Journal of Finance, American Economic Review, and Journal of Financial Economics and by practitioners at firms including BlackRock, Vanguard Group, Goldman Sachs, and Morgan Stanley.

History

CRSP was established in 1960 at the University of Chicago with support from faculty associated with the Cowles Commission and the Graduate School of Business to address the lack of systematic historical data for empirical research. Early collaborations involved scholars affiliated with Eugene Fama, Merton Miller, and Kenneth French and institutions such as the National Bureau of Economic Research and the Securities and Exchange Commission. During the 1970s and 1980s CRSP expanded coverage to include delisted securities and survivorship-bias adjustments, engaging with projects linked to Harvard University, Massachusetts Institute of Technology, and the Wharton School of the University of Pennsylvania. Subsequent decades saw productization and partnerships with vendors like Thomson Reuters, Bloomberg L.P., and CRSP/Compustat integrations with Standard & Poor's indices and NYSE archival feeds.

CRSP's core offerings include historical daily and monthly stock return series for equities traded on exchanges such as the New York Stock Exchange, American Stock Exchange, and NASDAQ, along with indices and capitalization data used by researchers at London School of Economics, Columbia Business School, Stanford Graduate School of Business, and Yale School of Management. Complementary products incorporate mutual fund databases cited in studies from Harvard Business School and regulatory analyses by the Securities and Exchange Commission. CRSP also provides event histories, identifier crosswalks used with Compustat, CRSP Survivor Bias Free Database, and linkage tables employed in projects at Princeton University and Northwestern University. Specialized datasets support work on factor models associated with Fama–French three-factor model research and portfolio attribution studies by firms like State Street Corporation and Blackstone Group.

CRSP employs procedures for return calculation, delisting adjustments, and share-weighted capitalization consistent with standards from committees and scholars at National Bureau of Economic Research, American Statistical Association, and research groups including Center for American Progress-affiliated teams. Data cleaning relies on corporate action event processing akin to methods used in datasets from Compustat, Thomson Financial Datastream, and Morningstar, Inc., with audit trails paralleling archival practices at the Library of Congress and the Chicago Historical Society. CRSP documents treatment of stock splits, dividends, mergers, and reclassifications, aligning with methodologies discussed in work by Eugene Fama, Kenneth French, Richard Roll, and James M. Poterba. Quality control is informed by comparisons against feeds from NYSE Arca, BATS Global Markets, and retrospective reconstructions similar to projects at Inter-university Consortium for Political and Social Research.

CRSP datasets have been cited extensively in empirical studies by scholars at Princeton University, Massachusetts Institute of Technology, Harvard University, Columbia University, University of Pennsylvania, and Stanford University. Landmark studies using CRSP data include research on market efficiency associated with Eugene Fama, asset pricing tests by Kenneth French, and corporate finance analyses that have appeared in the Journal of Finance and the Quarterly Journal of Economics. Industry practitioners at Goldman Sachs, Morgan Stanley, JPMorgan Chase, PIMCO, and BlackRock use CRSP for backtesting, risk modelling, and index construction. Policymakers at the Securities and Exchange Commission and analysts at Federal Reserve Bank of New York have referenced CRSP-derived evidence in regulatory reports and working papers.

Access to CRSP products is provided via institutional subscriptions at universities such as the University of Chicago, Yale University, Harvard University, Columbia University, and corporate clients including Bloomberg L.P. and Refinitiv. Licensing agreements govern redistribution and commercial use, with end users required to comply with terms similar to contracts used by ProQuest and EBSCO Information Services. Data delivery mechanisms include FTP, secure APIs, and vendor-supplied snapshots comparable to services from Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Users in academic settings often combine CRSP data with Compustat, WRDS, and proprietary datasets from firms like FactSet for replication studies and coursework at business schools such as Chicago Booth and Wharton.

CRSP is administered through the University of Chicago Booth School of Business with oversight from academic directors and advisory boards that have included faculty from University of Chicago, Harvard Business School, Stanford Graduate School of Business, and the University of Pennsylvania. Funding sources historically include institutional support, subscription revenues, and grants from organizations like the National Science Foundation and foundations supporting research such as the Ford Foundation and the Rockefeller Foundation. Partnerships with commercial vendors and data licensors such as NYSE, Nasdaq, Inc., and S&P Global contribute to operational sustainability and dataset enrichment.