Alan Greenspan in Sunday’s FT said the recent financial crisis may be judged in retrospect as “the most wrenching since the end of the second world war.”
“The essential problem,” he wrote, “is that our models — both risk models and econometric models — as complex as they have become, are still too simple to capture the full array of governing variables that drive global economic reality.”
Says Professor Paul Glasserman: “Mr. Greenspan’s article highlights the shortcomings in risk-management systems that result from limited historical data — particularly data from good economic times. Taking this point a step further, financial innovation can end up focusing — sometimes unwittingly — on the weak points in risk measurement. When correlations are misjudged, as in Greenspan’s example, the greatest strains get put on the weakest links.”
Photo credit: Toni Lozano
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Here's the question I've been trying to figure out about the financial crisis. What is it that causes so many well-trained individuals on Wall Street, many of whom are products of top-ranked business schools like our own, to make the kinds of high-risk investment mistakes that are coming to light? Is it, as Paul suggests, incomplete models of risk measurement? Or is it a good old-fashioned case of collective irrationality born of the idea that our financial markets are rational? Or is turning a blind eye to risk the flip side of greed?
I believe financial crisis, such as the one currently being faced by the US economy, are born of an over reliance on systems and models and less use of rational thought. Today's professionals are not thinking as hard as people in the same positions used to, say 10, 15 years ago. Models and tools of risk management have made us derelict in our duties; we have forgotten that they are merely meant to enhance the decision making process, not constitute it fully. If we could all take a step back once in a while and evaluate our actions from all angles, then maybe such crises would remain a thing of memory.
Agreed fully Terry. Quantiative risk management models capture events based on availability of historical data and may assume parametric distributions in most cases (even simulations are calibrated based on historical information) - therefore these are inherently retrospective models, which often miss out fat-tails due to human behavior. In our current situation, the moral hazard issues we see in consumer lending constitute exactly that sort of phenomenon. And it goes to demonstrate the importance of combining intuition with quantitative modeling and the challenges we continue to face in balancing financial innovation with business ethics.
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