mathbabe

After the credit crisis hit we all realized that there’s a lot more risk out there than can be described by trailing volatility measures.  Once I decided to leave the hedge fund world, I was thinking about working for the “other side,” namely to help quantify risk and/or work on the side of the regulators.  I applied to the SEC, the New York Fed, and Riskmetrics, a software company which had a good reputation.  I never heard from the Fed, and the SEC didn’t seem to have something for me, but I landed a job at Riskmetrics.

I figured it this way: if you work on a risk in a good way, if you make a better risk model, then you can at least argue you are improving the world.  If you are instead making a bad risk model, and you know it, then you’re making the world a worse, riskier place.  For example if you are working for a rating agency and get paid to ignore signs of riskiness, then that would be the not improving the world kind.

I really enjoyed my job, and after some months I was put in charge of “risk methodology,” which meant I got to think about how to quantify risk and why.  I worked on our credit default model, which was super interesting, and I got to talk to the head trader of one of the biggest CDS trading desks regularly to understand the details of the market.  In fact many of the biggest hedge funds and banks and pension funds send their portfolios daily to companies such as Riskmetrics to get overnight assessments of the riskiness of their portfolios.  Bottomline is that my job kind of rocked, but it didn’t last forever; we were acquired soon after that by a company which didn’t offer me the same kind of position and I left pretty soon.

Here’s an article that very clearly articulates some of the problems in the field of quantitative risk.  In my opinion it doesn’t go far enough with respect to their last point, or maybe it misses something, where they talk about “forecasting extreme risks.”  This refers to the kind of thing that happens in a crisis, when all sorts of people are pulling out of the market at the same time and there are cascading, catastrophic losses.

What gets to me about this is that everyone talks about moments like these as if they can’t be modeled, but of course they can be, to a limited extent.  Namely, although we don’t know what the next huge crisis will be, there are a few obvious candidates (like the Greek, Portuguese, Irish, or U.S. defaulting on their debt) which we should be keeping an eye on to the best of our quantitative abilities.  Many of the “panic” situations (like the mortgage-backed securities debacle) were pretty obvious risks weeks or months in advance of their occurring, but people just didn’t know how to anticipate the consequences.  That’s fine for a given individual trader but shouldn’t be true for the government.

I think the first step should be to compile a longish list of possible disaster scenarios (include the ones we’ve already seen happen) and decide what the probability of each scenario is- these probabilities can be updated each week by a crew of economists or what have you.   Secondly and separately, set up a quantitative model which tries to capture the resulting cascade of consequences that each scenario would create;  this would be complicated and involve things like guessing the losses at which hedge funds start liquidating their books, but should be aided by amassing huge amounts of information of the underlying portfolios of the largest institutions.

In my opinion the regulators have made a huge mistake in the past three years by _not_ insisting on getting the entire portfolio from every major hedge fund and bank every night (which from above we know is possible for them since they already send them to Riskmetrics-like software companies, although I’ve read articles where they claim this would be way too onerous a task) and, with that deep information, model the effect of a crisis scenario from our above list;  how would it affect the bond market?  The CDS market?  The model which already exists at quantitative hedge funds now, which measures the impact and decay on trades, is a great start. Moreover, this model is not impossible to train (i.e. the actual coefficients inside the model’s formulas aren’t that hard to estimate), in fact it wouldn’t be that big a deal if we had as much data as I’m talking about.  To me it’s unbelievable that we aren’t getting this portfolio information every day (or even intraday) and creating a “systemic impact model,” because it would clearly make us better prepared for future events (although not of course perfectly prepared)  and no hedge fund or bank could argue that we shouldn’t be worried – it should be one of the costs of doing business on Wall Street.