Operations research and hard systems modeling are neat. The only gripe I have is that often times the models make simplifying assumptions which hold tenuously

Operations research and hard systems modeling are neat. The only gripe I have is that often times the models make simplifying assumptions which hold tenuously at best. One example of this is the Gaussian copula used in VAR. In actuality, neither the marginals nor the copula are Gaussian in the large majority of cases; they ARE stable distributions, but the tails can be absolutely HUGE. The Gaussian distribution is attractive because it is well behaved, and in most cases we don't have enough observations to properly understand the full tail structure of the underlying distribution. As a result, you get quants that make a model and call a small subset of points (which are completely valid) "outliers". Then when we observe the tails of the distribution, things fall apart because over-leveraged bankers made decisions based on the notion that the model accurately reflected reality.