Wall Street runs on models. Indeed one could argue that the misapplication of models helped cause the financial crisis. As Felix Salmon wrote back in 2009:
In the world of finance, too many quants see only the numbers before them and forget about the concrete reality the figures are supposed to represent. They think they can model just a few years’ worth of data and come up with probabilities for things that may happen only once every 10,000 years. Then people invest on the basis of those probabilities, without stopping to wonder whether the numbers make any sense at all.
Emanuel Derman in his new book explores the topic of models in some depth including “The Financial Modeler’s Manifesto” in which he notes the ways in which we can use models “wisely and well.” The problem is that on Wall Street the modeling is often created in reverse order. The product comes first and then the model. In this scenario the model need not be well-constructed, but simply good enough. Derman writes:
Similarly, I believe that the designers of financial products should create securities whose purpose, exposure and risks are clear. Unnecessarily bundled complex products whose risks are obscure are often more profitable for the firms creating them than simple ones because their value is hard to estimate. If products were transparent, good modeling would be easier.
As Derman notes models are entrenched on Wall Street. The challenge as David H. Freedman notes is that as models become more complex the harder it is for all of the parties involved to understand them. The global financial system has become so complex and so model-dependent it is hard to break out of that mentality. He writes:
It’s a safe bet that financial risk models will remain unreliable for years to come. So what should we do about it? The only real option is not to trust the models, no matter how good the equations seem to be in theory. Such thinking, though, conflicts with the core ethos of Wall Street. “There has never been any incentive to distrust the models because the people in control keep making lots of money using them,” Jarrow says. “Everyone thought the models were working right up until the crisis. Now they’re trusting them again.” The models and data are likely to improve, he asserts, but not enough to justify much faith in the results.
The financial system runs on models, therefore the models used on Wall Street, however imperfect and fragile, aren’t going anywhere. Understanding the state of modeling is a first step. The much harder step is to put in place models that explain reality as opposed to creating their own reality.
The formula that killed Wall Street. (Wired)
An excerpt from Emanuel Derman’s Models.Behaving.Badly: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life on understanding the limits of models.* (Institutional Investor)
*Amazon affiliate. You know the drill.