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Financial Markets: Loving the Data

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Over the past half-century, in the United States and many other countries, financial markets have acquired enormous importance and power. Winning public support for this shift was a difficult battle: in the wake of the Great Depression, the general public identified finance with speculation and reckless risk-taking, and financial markets seemed particularly suspicious because they were unpredictable—they looked more like casinos than a reliable source of opportunities for investment, the kind of place where working families could let their hard-earned savings grow safely. 

The Ascent of Market Efficiency: Finance That Cannot Be Proven traces how this battle was won intellectually—and how financial economists acquired scholarly legitimacy and professional power. Beginning in the 1950s, these US-based scholars formed a new discipline and dedicated it to the statistical study of financial markets: the new, self-described science of financial economics developed around the very notion that had generated such resistance—on unpredictability itself. Financial economists began describing and modeling unpredictable markets as efficient markets: when free of unwanted interference, and especially when unhampered by the intrusion of regulators and governments, markets would quickly become the best arbiters of value, or so they argued, because no other expert could possibly have a better answer. How did financial economists arrive at this remarkable conclusion, even in the face of skepticism, not just from the general public, but from within their own ranks? 

How did financial economists arrive at this remarkable conclusion, even in the face of skepticism, not just from the general public, but from within their own ranks? 

The book tells the story of this evolution, focusing on three basic moves. 

1. Overcoming data skepticism

From scholars writing in professional outlets to maverick scientists like Benoit Mandelbrot, the idea that one could understand financial markets by analyzing increasingly accessible, computerized datasets collecting price movements in financial securities encountered strong resistance. How would the analyst know that the data were not affected by long-term cycles that the existing temporal framework did not capture? What if the data-generating process was flawed or misunderstood? Yet, much like today’s big data, statistical series on financial securities proved to be irresistible. Eugene Fama, widely described as the father of modern finance, based his award-winning work on efficient markets on data analysis. 

2. Defeating theory

The strongest ammunition against reliance on data as a way to understand financial markets was in the hands of more theoretically oriented economists, like Fischer Black, who saw empirically-based generalization devoid of theory as nothing more than data-dredging. Once again, the allure of the computerized dataset was too strong. Data analysis, which included recording, formatting, and manipulating the data, provided more than sufficient work to aspiring economists. Theory development did not.

3. Loving the data

As they put data on financial securities as the very center of their research agenda, financial economists developed a set of values—reasonability, incrementalism, collaboration—that turned computers and data from technical tools useful to achieve their research goals, to markers of belonging to a new research community: they became symbols of the discipline, to which financial economists would show loyalty and even affection. Data came to be seen as sources of creativity, discovery, and professional identity.     

The rise of financial markets is not just the result of the disciplinary success of financial economists. But understanding how this group of experts came together in support of the proposition of market efficiency, tells us something important about the power of intellectual communities, and the emergence of new ways of producing knowledge. Watching a new and powerful discipline develop around data analysis gives us new insight into deep questions about knowledge, especially in our data-saturated, contemporary society.

The rise of financial markets is not just the result of the disciplinary success of financial economists. But understanding how this group of experts came together in support of the proposition of market efficiency, tells us something important about the power of intellectual communities, and the emergence of new ways of producing knowledge.


Simone Polillo is Associate Professor of Sociology at the University of Virginia. He’s the author of Conservatives vs. Wildcats: A Sociology of Financial Conflict (Stanford, 2013) and has published in the American Sociological Review, the American Journal of Sociology, Theory and Society, and the Journal of Cultural Economy, among others.

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