In November a curious paper dropped on SSRN, an online hub widely used by economists to circulate their work. The paper’s authors are two of the most important figures in academic finance: Kenneth French, of Dartmouth College’s Tuck School of Business, and Eugene Fama, a Nobel Prize-winning economist from the University of Chicago. The article itself seems modest, reading like a technical footnote to research the duo published 30 years ago, about stock market returns.
Without context, “Production of U.S. Rm-Rf, SMB, and HML in the Fama-French Data Library” is a bit mystifying. The paper seems to be answering questions about Fama and French’s data—yet it doesn’t spell out what the questions are or who’s asking them. To understand its 18 pages, one might need a Ph.D. in finance. To read the subtext, you’d have had to know a few dozen people with one. The paper is the culmination of a quiet but sharp-elbowed debate in a corner of academic economics about the reliability of a dataset that’s crucial not only to professors and grad students but also to professional traders, investors, securities litigators and corporate executives.
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