The abstract alone should whet your appetite:
The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems—and financial markets in particular—that are as predictive as those in physics. While this perspective has led to a number of important breakthroughs in economics, “physics envy” has also created a false sense of mathematical precision in some cases.
We speculate on the origins of physics envy, and then describe an alternate perspective of economic behavior based on a new taxonomy of uncertainty. We illustrate the relevance of this taxonomy with two concrete examples: the classical harmonic oscillator with some new twists that make physics look more like economics, and a quantitative equity market-neutral strategy. We conclude by offering a new interpretation of tail events, proposing an “uncertainty checklist” with which our taxonomy can be implemented, and considering the role that quants played in the current financial crisis.
Most fascinating to me is the part where levels of uncertainty are discussed, from Level 1 (complete certainty) to Level 5 (irreducible uncertainty). This expands on and refines Frank Knight's distinction between risk, where classical statistical theory applies, and uncertainty, where it does not, a distinction that, incidentally, lies at the center of Nassim Taleb's thinking.
In a coincidental nod to the concept of dream levels versus reality as brilliantly imagined in the movie Inception, this is how "Level 4" uncertainty is described:
Continuing our descent into the depths of the unknown, we reach a level of uncertainty that now begins to separate the physical and social sciences, both in philosophy and model building objectives. By Level-4 or “partially reducible” uncertainty, we are referring to situations in which there is a limit to what we can deduce about the underlying phenomena generating the data.
As for "Level 5" (i.e. irreducible) uncertainty, it is:
the polite term for a state of total ignorance; ignorance that cannot be remedied by collecting more data, using more sophisticated methods of statistical inference or more powerful computers, or thinking harder and smarter. Such uncertainty is beyond the reach of probabilistic reasoning, statistical inference, and any meaningful quantification. This type of uncertainty is the domain of philosophers and religious leaders, who focus on not only the unknown, but the unknowable.
