The discussion on why Apple is cheap was very useful. The debate brought into focus the possible causes for pessimism in the face of overwhelming evidence to the contrary. But maybe there is yet another explanation. The way the data was presented was as a difference between historic and projected growth rates. Is this the way analysts actually think?
Perhaps they don’t project growth based on historic growth, but project earnings given historic earnings. In other words they don’t look at the first derivative (change in earnings) but the shape of the actual data.
The following chart shows that data, i.e. forecasts as an extension of a sales trajectory. The blue area are actuals and the grey branches show projections at a given end of fiscal year.
Seen this way, we can imagine how the projections can be considered “reasonable”. Some appear to be linear extrapolations while others show up as the end of “S-curves”.
What none of them imply is exponential growth. But would forecasting exponential growth be considered reasonable? Clearly not since it’s never been consensus. But disruptive companies do follow non-linear growth. In fact, every company that has gone from being small to being big (which is to say all large companies) went through non-linear growth phases. The “natural” shape of growth is exponential.
The failure is therefore not of reason but of failing to use a model that assumes acceleration of sales. I believe that institutional financial advisors are conditioned (or coerced) into assuming that nothing unreasonable ever happens. That seems like a completely flawed foundation to stand on.
- This post is inspired by the New York Times chart showing budget forecasts.
- The same data shown on a log scale: