Originally published June 2005
The Folly of Forecasting
06/07/05 – 01:05 PM EDT
As a chartered member of the chattering class, I am all too familiar with the “perils of predictions.” Anyone who works in the financial field and speaks to the press eventually gets tagged for a market forecast gone awry. It’s an occupational hazard.
Unfortunately, investors all too often give these “predictions” in print or on TV far more weight than they should. It’s very easy for a confident-sounding analyst, fund manager or professor to say something on TV that can throw off the best laid plans of investors.
I wish an SEC-mandated disclosure accompanied all pundit forecasts: “The undersigned states that he has no idea what’s going to happen in the future, and hereby declares that this prediction is merely a wildly unsupported speculation.”
Don’t hold your breath waiting for that to happen.
The bottom line is that I’ve yet to find anyone who can accurately and consistently forecast the market behavior with any degree of accuracy, beyond short-term trend following. That inconvenient factoid never seems to dissuade the prophets — or the press — from their fortune-telling ways.
There are a few things that investors should keep in mind when encountering these speculations. Whenever you find yourself reading (or watching) someone who tells you where a stock or the markets are going, consider these factors:
Looking at the future in terms of various probabilities is a productive way to position assets and manage risk. Why? If your expectations for the future recognize that this is but one possible outcome, then you are more likely to consider and plan for other contingencies. It builds in an expectation that other scenarios can and will occur.
For example, one signal I use is to determine when to sell (the subject of a future column) is after a long uptrend is broken. It’s not that stocks cannot go higher after breaking their trend line — they sometimes do. However, most of the time this happens it signals a significant change in institutional behavior towards the stock. Typically, it reflects a shift from fund accumulation to distribution.
For those people who have been enjoying the ride in Google (GOOG) — especially the near vertical move since April — this is a high probability strategy. Once that trend line gets broken, say adios muchachos, take your profits and move along.
Again, a trend break is not a guarantee that the upside is finished, but it’s a fairly good probability assessment.
The second type of good prediction is the risk-based discussion. These forecasts care less about price targets — instead, they are an assessment of danger. In other words, to buyers of stocks under the present conditions, when this, that and the other are happening, you are taking on more (or less risk) than is typical. Saying the markets contain more or less risk at given times is a very different statement than: “I think the Dow is going to go to X.”
I engaged in a combination of broader market-based probability this week in Smart Money, along with future risk assessment. Given the change in character the market displayed since the April lows, I noted the high probability of a substantial rally in the second half of the year. My basis for this was part technical — the market regaining its prior trading range — and part anecdotal (all the hedge fund cash on the sidelines). This created a high probability of a move similar to what we saw over the summer of 2003.
But I also included a risk-based assessment based upon the age of this bull move, along with the decaying macroeconomic environment; in tandem, they set up an increasing risk environment as the year progresses. That’s how a top can form, and that presents an increased risk of a market correction or even collapse.
When you stop to consider all of the unforeseen actions that might occur between now and then, however, it becomes pretty apparent that all forecasting is at best a low probability activity.
Why are the markets so difficult to predict? To borrow a phrase from the physicists, the market demonstrates “unstable aperiodic behavior in deterministic nonlinear dynamism.”
This behavior is better known as Chaos Theory.
What does that mean in English? The market is called “aperiodic” because it never repeats itself precisely the same way. Weather is also aperiodic — it may be colder in the winter than in the summer, so there is a degree of cyclicality. But the day-to-day changes are never exactly the same year after year. The same dynamic applies to the markets: There are similarities from one era to another, but it’s never identical. In Mark Twain’s words, “History doesn’t repeat, but it rhymes.”
The markets also act with a surprising degree of instability. Small forces can create disproportionately large reactions. A surprising economic report, an off-the-cuff comment by a Fed official, a small change in earnings by any one of 1,000 companies; any one of these data points can roil the market. That behavior does not occur in what the scientists call “stable” systems.
Given the complexity of both the capital markets and the physical universe, we shouldn’t be that surprised that Chaos Theory is so applicable to the financial markets.
Considering how little we know about the totality of market conditions — and how incredibly intricate and complex the system is — it’s no surprise that pundit predictions are so frequently poor.