Unknown Unknowns: Predicting Stock Trends
NEW YORK (TheStreet) -- How significant to you is it that Wall Street strategists have lowered their equity market forecasts from mid-double-digit returns for 2013 to single-digit returns for 2014?
It turns out that those forecasts are worth a lot less than you might think.
Equity-return modeling generally incorporates estimating the average trend in economic factors, and then assigning a price multiple to that future trend. (The new price multiple is almost always anchored within 1 or 2 of the current multiple). To add some complexity, in the recent bull market leading up to the 2008 to 2009 financial crisis, Wall Street firms opened up this single-point price target. Some major firms now offer binomial path outcomes instead -- a bull case and a bear case scenario, with a probability assigned to each.
Most people -- including the strategists themselves -- focus on such important details. But these probabilities could be risk-adjusted so that the future price can be extrapolated using a risk-neutral investor approach, or the actual probabilities could stay in absolute terms and an appropriate risk rate could be used to determine the future price target.
Leaving this whole complication aside, the point here is that the major source of uncertainty among Wall Street forecasters remains on macro calls of what the price multiple would be on the future earnings trend. Are they generally optimistic or generally pessimistic? This can account for a large explanation of the generally double-digit difference in the higher year-end targets versus the lower year-end targets. If the current multiple is, for example 15, and a pessimist anticipate a 0.5 change and an optimist estimated a 2.0 change, then the 1.5 difference is 10% of the original 15. This is an important idea, as we uncover an additional 12%-or-so spread that risk mis-timing forces onto things.The core middle-of-the-pack entered this year looking for a single-digit return in 2014. Of course, as any long-term strategist outside of Wall Street would note, the end of 2014 is quite an arbitrarily brief period of time. And these net returns just take into account a long-run average amount of risk within that period. Of course this masks an ugly truth about the nature of risk, which is that it doesn't occur in the same way and time frame as the economic return factors that monopolize the intellectual demands of Wall Street analysts. Now let's assume that the major risks implicit in each calendar year are one 10% correction and two 5% corrections -- 20% annual total, 40% biennial. But in reality, these corrections will happen when they choose. They are calendar agnostic and do not conform to the smooth parameters of economic growth extrapolations. Looking at the probability of the risk convolutions for any one given year, we can suggest the other combinations that can play out in our hypothetical scenario of 40% biennial risk. Namely look at these other examples, which could occur in 2014 and 2015 (including in reverse order, so that either year could be Year A, and the other be Year B). Any event that shifted from Year A, to Year B, is italicized. The probabilistic weight is provided above each combination. The ordering of the risk events in any given year is irrelevant.
So if there is 40% biennial risk, then that could be distributed as follows.
Year A --> -10%, -5%, -5%
Year B --> -10%, -5%, -5%
Year A --> -10%, -5%
Year B --> -10%, -5%, -5%, -5%
Year A --> -5%, -5%
Year B --> -10%, -5%, -5%, -10%
Year A --> -10%
Year B --> -10%, -5%, -5%, -5%, -5%
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