A thought about risk

Andrew Lo has an interesting talk posted by MIT in which he sets forth a taxonomy of uncertainty and risk, crossed with levels of action. He suggests that physics is a field in which 3 laws are enough to predict 97 percent of what is of interest to physicists, while economics is a field where 97 laws are enough to predict 3 percent of what interests economists.

I got lost in the discussion thinking about whether it is the same to bet $5,000 on the flip of a coin, or to give someone $5,000 and get either nothing or $10,000 back according to the flip of a coin. Of course, from a formal point of view the bet is the same, but somehow it doesn't seem the same. In discussing the bet, Lo doesn't focus on the fact that people are risk adverse, and that they hate to give up what they already have.

Lo's fundamental point is that economic models that were originally postulated for academic (and didactic) purposes are used in the real world. Indeed, it has been charged that the quants who developed models for making bets in the financial world assumed too often that those models were good predictors of behavior, and we all got into trouble when investors got into behaviors at the bursting of the real estate bubble that was not accurately predicted by the equations.

Now I was trained as an engineer, and engineers can be seen as our means of reducing uncertainty. Think about auto transportation. A century ago, auto transportation was a risky business. Now automotive engineers have produced auto drive trains that companies can guarantee for five years or 50000 miles. Automobile tires last reliably for tens of thousands of miles. The engineers have developed seat belts and air bags that make survival of crashes more likely even in the increasingly rare events of auto crashes. Civil engineers have developed roads that not only reduce the likelihood of breakdowns and punctures, but which reduce the probability of accidents. The improved reliability of aircraft is even more notable.

Some of the techniques to reduce uncertainty are brute force. When designing a structure, engineers will figure out how much steel to use to carry the heaviest expected loads, and then they will multiply the strength in the design to achieve a safety factor.

It seems to me that we need "financial engineers" to design financial instruments and systems to reduce uncertainty. Lo pointed out that actuarial analysis seems able to do this for life insurance. Perhaps we could apply the same approach to other financial matters.