Boeing's Misstep Is Indicative of Broader Misconceptions of Risk

| About: The Boeing (BA)

In an announcement made to the chagrin of its credibility, Boeing Co (NYSE: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.

The specifics of Boeing's troubles were outlined in a WSJ article from yesterday's paper, which cited the difficulties associated with certain carbon-fiber composite parts as the Company's primary stumbling block. The composite parts, desirable partly because of their light weight, pose an interesting problem for airline manufacturers: Advanced computer models display an inability to accurately predict the behavior of these composites under actual flight conditions. While the laws of physics and the elemental composition of the metals lend themselves to calculable outcomes under laboratory conditions, there is something about the introduction of real wind, velocity, acceleration etc. that defies the computer's ability to conduct its "stress tests".
In his new book Shopclass as Soulcraft: An Inquiry Into the Value of Work , Matthew Crawford addresses this phenomenon by referencing some wisdom he once received from his mathematically inclined father. The gist of this wisdom was that a shoelace knot, by all mathematical accounts, could always be untied by tugging at a single end of the knot. Even at a young age, Crawford was able to identify the inherent shortfalls of his father's statement; namely that while the conclusion might be valid under perfect conditions, it largely ignored the possibility that a shoelace might be wet, or compromised in some other way as to negate its "easy removal" property.
Unfortunately, such blind reliance on mathematical assumptions is not limited to shoelaces. As evidenced by Boeing's costly delays, airline manufacturers have come to rely heavily on computer models whose predictions apparently fail to capture real world variables. Furthermore, there is an argument to be made that an over reliance on computer driven and mathematical models, in an attempt to capture the elusive concept of "risk", has contributed to the current state of financial markets and the economy.

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.

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