In an announcement made to the chagrin of its credibility, Boeing Co (BA) revealed that the 787 Dreamliner's maiden flight would once again be delayed, due primarily to issues surrounding the proper attachment of the aircraft's wing to its body. This revelation prompted a round of excoriating commentary, accompanied by the necessary downward revisions to earnings estimates, from several equity analysts.
Although management will bear the brunt of the fallout from the Dreamliner misstep, we would not characterize the embarrassing event as being indicative of Boeing's inability to manage a new product from conception to delivery, but rather as an over reliance on computer driven models - a condition that parallels many aspects of the current US economic predicament.
We will first clarify our position on this matter by stating that we are not categorically opposed to the use of quantitative models as a risk measurement tool, provided that the user of the said tool has sufficient respect for the model's fallibility. Additionally, we acknowledge the argument that, in the midst of pursuing financial gains, individuals or organizations will often choose to ignore sobering evidence, and in some cases manipulate the means by which said evidence is generated altogether. However, we would observe that the point at which computer based and statistical models are the most vulnerable, i.e. most susceptible to providing an incorrect prediction, is the point at which the model meets reality. Boeing's moment of realization arrived when its composite parts were introduced to climatic and environmental variables that simply do not exist in the vacuum of computer models.
For those involved in the securitization of sub prime mortgages, and in particular those who either constructed or trusted the models which purported to predict default / delinquency / foreclosure rates across a pool of mortgages, the fact that something went wrong has been apparent for some time now. The historical data that guided mortgage performance projections was collected during both economic expansions and recessions, but never during an expansion that was accompanied by a housing boom of such colossal proportions. As speculative purchases proliferated, human nature introduced a wild-card to the equation that the models had not foreseen: Many homes were purchased with the intent to make a quick profit, and many of those buyers were ready, willing and able to stop servicing their mortgages when it became apparent that those profits would not materialize.
The widespread development of this mindset was the point at which the computer models were faced with a reality that did not conform to their view of the world. Models based upon the assumption that the risk and return of a financial time series is normally distributed are potentially best suited for markets dominated by professionals, having a predictable and uniform set of goals and responses.
However far removed a mortgage may be from the original loan underwriting decision, it can never escape the fact that an individual must continue to remit payment on a monthly basis. Whether it be shoelaces, composite material used in airline construction, or the performance of speculative mortgages, the important thing to acknowledge, and respect, is that aspects of this world will continue to defy prediction via statistical and computer based assignments of probability.
Disclosure: No position in any securities mentioned. The author does not stand to benefit in any way from the sale of Matthew B Crawford's book.