For years, academic experts have championed the widespread adoption of the “Fama-French” factors in legal settings. Factor models are commonly used to perform valuations, performance evaluation and event studies across a wide variety of contexts, many of which rely on data provided by Professor Kenneth French. Yet these data are beset by a problem that the experts themselves did not understand: In a companion article, we document widespread retroactive changes to French’s factor data. These changes are the result of discretionary changes to the construction of the factors and materially affect a broad range of estimates. In this Article, we show how these retroactive changes can have enormous impacts in precisely the settings in which experts have pressed for their use. We provide examples of valuations, performance analysis, and event studies in which the retroactive changes have a large—and even dispositive—effect on an expert’s conclusions.
Securities Law
This Essay argues that the increasing prevalence and sophistication of artificial intelligence (AI) will push securities regulation toward a more systems-oriented approach. This approach will replace securities law’s emphasis, in areas like manipulation, on forms of enforcement targeted at specific individuals and accompanied by punitive sanctions with a greater focus on ex ante rules designed to shape an ecology of actors and information.
The global financial crisis was much more than a disaster for banks.