"When there's uncertainty, they always think there's another shoe to fall. There is no other shoe to fall." -- Kenneth Lay, former CEO of EnronInvesting deals with both risk and uncertainty. In 1921, University of Chicago professor Frank Knight wrote (he is not the publisher) the classic book Risk, Uncertainty, and Profit. An article from the Library of Economics and Liberty described Knight's definitions of risk and uncertainty as follows: "Risk is present when future events occur with measurable probability. Uncertainty is present when the likelihood of future events is indefinite or incalculable." In some cases, we know the odds of an event occurring with certainty. The classic example is that we can calculate the odds of rolling any particular number with a pair of dice. Because of demographic data, we can make a good estimate of the odds that a 65-year-old couple will have at least one spouse live beyond age ninety. We cannot know the odds precisely because there may be future advances in medical science extending life expectancy. Conversely, new diseases may arise, shortening it. Other examples of uncertainty: the odds of an oil embargo (1973); the odds of an event such as the attacks of Sept. 11, 2001; or the odds of an accounting scandal the size of Enron. That concept is uncertainty. It is critical to understand the important difference between these two concepts: risk and uncertainty. Consider the following example. An insurance company might be willing to take on a certain amount of hurricane risk in Dade and Broward counties in Florida. They would price this risk based on perhaps 100 years of data, the likelihood of hurricanes occurring and the damage they did. But only a foolish insurer would place such a large bet that the company would go bankrupt if more or worse hurricanes occurred than in the past. That would be ignoring the uncertainty about the odds of hurricanes occurring: The future might not look like the past.
Efficient Frontier ModelsTo assist in the development of investment plans some investors and many advisers use what are called efficient frontier models. Harry Markowitz first coined the term "efficient frontier" almost 40 years ago. He used it to describe a set of portfolios with the highest expected return for each level of risk. Today, many efficient frontier programs are available. They begin with individual investors answering questions about their risk profiles. The program then generates a portfolio consisting of various asset classes delivering the greatest expected return given the individual's risk tolerance. Sounds like a wonderful idea. The problem is understanding the nature of an efficient frontier model and the assumptions on which it relies. As with a sophisticated racing car, a powerful tool in the wrong hands can be a very dangerous thing. Efficient frontier models attempt to turn investing into an exact science, which it is not. For example, it is logical to believe that in the future, stocks will outperform fixed income investments. The reason is stocks are riskier than risk-free Treasury bills. Investors will demand an "equity risk premium" to compensate them for this risk. While the past may be a guide to the size of the equity risk premium, the bull market of the 1990s and bear markets of 2000-02 and 2008 demonstrate that it is no guarantee. The equity risk premium is not constant. From 1927 through 1999, the equity risk premium was 6.8%. By the end of 2002, it had fallen to 5.7%. By the end of 2007, it was back up to 6.1%. And by the end of 2008, it had fallen to 5.4%. We shall see that even relatively small changes to the inputs are very important when it comes to efficient frontier models.