11/18-19/2019 When Data Goes to the Market

DISCUSSION NOTES BY CANAY ÖZDEN-SCHILLING:

We put together this mini movie festival to complement our data & finance theme this semester. The three movies we picked were blockbusters that were also critically acclaimed; along with the popcorn, they made good material for a fun, undergraduate-friendly conversation. The screening of our first movie of the series, the Big Short, was complemented by a discussion moderated by Floyd Norris, a former financial correspondent for the New York Times and a current lecturer in the Economics Department at JHU. As moviegoers might remember, the Big Short is based on a non-fiction book that focuses on a number of traders who, in anticipation of the 2008 financial crisis, bet against “collateralized debt obligations”—the offending product of the bubble that eventually burst—and made tremendous profit along the way. Norris considers the movie a very accurate depiction of the financial landscape prior to the collapse—full of low-level fraudsters and poorly informed observers, including journalists, economists, and regulators. In the way risk was transferred from people who understood it to people who didn’t, what played a particular role was how data was used; while individual players crunched numbers to identify profit opportunities, rating agencies could only check deals after executed and no one seemed interested in identifying ominous macro trends. As we see in the movie, even those protagonists who had foresight (and used that foresight towards individual profit) came close to being right and broke, because the market wouldn’t collapse as soon as they thought. “The graves of Wall Street,” Norris remarked, “are filled with people who were right too soon.” The 2008 financial crisis is still with us (even though the undergraduates in the crowd understandably had hard time remembering its specifics) since areas hit hard by foreclosures are still recovering and the few good reforms that followed the crisis are now being pecked at by the present administration.


Our morning session was followed by an afternoon screening of Moneyball—a fascinating account of how sport statistics began to eventually take over baseball early in the present century. Our discussion was moderated by Eli Katz, a senior undergraduate in Applied Mathematics and Statistics, who also has had professional experience in sports analytics and is headed towards a career in the field. Katz cited Moneyball as a first influence in picking this path, growing up as a kid who liked mathematics and baseball. The movie captures the moment of dataification in baseball, where scouting began to move away from observing players’ bodily characteristics and towards reading statistics generated about them to anticipate their potential. As the movie shows, the Oakland Athletics team embraced the statistical approach mainly to accommodate its small budget; as Katz discussed, however, analytics is now predominant and access to superior analytics is itself prized. The notion of accessing knowledge about oneself that is not otherwise accessible through experience or visual observation may be widely accepted now, thanks to, for instance, wearable technologies that surround us—yet the notion was not so commonly experienced at the moment and it inevitably offended sports executives who trusted their non-numerical observation skills. We discussed how, in many fields, dataification means the proliferation of experts who are less familiar with the subject at hand than they are with data. Katz helpfully disabused us of this assumption by discussing analytics professionals’ enthusiasm and profound intimacy with the sport.


The next day we continued our series with an afternoon screening of Margin Call, once again alongside generous servings of popcorn. Margin Call chronicles an unnamed investment bank’s actions in the lead-up to the financial crisis. After a few junior analysts realize the toxicity of the assets the firm is sitting on, the firm dumps those assets in a 24-hour sale before the market catches up to the firm’s objective, limiting the firm’s exposure and turning a good profit in the meantime. The movie surveys a wealth of characters, from junior analysts who knew they would lose their job but expected a hefty severance check, to risk management officers who hoped they would not be the one to be sacrificed as the scapegoat—characters who are all caught up in the constant expectation of layoffs, as well as huge bonuses handed out for accepting the moral burden of ruining unsuspecting people. Perhaps the most intriguing aspect of the movie was this rich characterization of an amoral (and not necessarily immoral) environment, where it is expected that each player would not hesitate to take their turn to try for their big day—where it is not considered the end of the world to destroy one’s trustworthiness in the industry and relationship with counterparties. Drawing comparisons with the medical field in the US, where layoffs are a multi-step, painstaking business, the audience wondered what makes this exceptional sense of uncertainty acceptable to its participants. As discussant, I was compelled to evoke social studies of perpetual downsizing and precarity in trading cultures (as evidenced by the work of anthropologists like Karen Ho), which bankers and traders may then disseminate onto the larger economy, in the sincere belief that precarity ultimately makes for resilience regardless of the context.
We ended our mini festival hoping for more viewings of this kind—entertainment with an eye for our recent socioeconomic histories and intimacy with data.

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