Share Price Behavior  729
Suppose you are valuing a company that seems to be at a peak in its earn-
ings cycle. You will never have perfect foresight of the market cycle. Based 
on past cycles, you expect the industry to turn down soon. However, there 
are signs that the industry is about to break out of the old cycle. A reasonable 
valuation approach, therefore, would be to build two scenarios and weight 
their values. Suppose you assumed, with a 50 percent probability, that the 
cycle will follow the past and that the industry will turn down in the next year 
or so. The second scenario, also with 50 percent probability, would be that the 
industry will break out of the cycle and follow a new long-term trend based 
on current improved performance. The value of the company would then be 
the weighted average of these two values.
We found evidence that this is, in fact, the way the market behaves. We 
valued the four-year cyclical companies three ways:
1. With perfect foresight about the upcoming cycle
2. With zero foresight, assuming that current performance represents a point 
on a new long-term trend (essentially the consensus earnings forecast)
3. With a 50/50 forecast: 50 percent perfect foresight and 50 percent zero 
foresight
Exhibit 37.5 summarizes the results, comparing them with actual share prices. 
As shown, the market does not follow either the perfect-foresight or the zero-
foresight path; it follows a blended path, much closer to the 50/50 path. So the 
EXHIBIT 37.5  Market Values of Cyclical Companies: Forecasts with Three Levels 
of Foresight
0
0.5
1.0
1.5
2.0
2.5
8
7
6
5
4
Years
3
2
1
0
Zero
foresight
50/50
Actual
share
price
Perfect
foresight
Index

730  Cyclical Companies
market has neither perfect foresight nor zero foresight. One could argue that 
this 50/50 valuation is the right place for the market to be.
An Approach to Valuing Cyclical Companies
No one can precisely predict the earnings cycle for an industry, and any single 
forecast of performance must be wrong. Managers and investors can benefit 
from following explicitly the multiple-scenario probabilistic approach to valu-
ing cyclical companies, similar to the approach used in Chapter 16 and the 
high-growth-company valuation in Chapter 36. The probabilistic approach 
avoids the traps of a single forecast and allows exploration of a wider range 
of outcomes and their implications.
Here is a two-scenario approach for valuing cyclical companies in four 
steps (of course, you could always have more than two scenarios):
1. Construct and value the normal cycle scenario, using information about 
past cycles. Pay particular attention to the long-term trend lines of oper-
ating profits, cash flow, and return on invested capital (ROIC), because 
they will have the largest impact on the valuation. Make sure the con-
tinuing value is based on a normalized level of profits (i.e., a point on 
the company’s long-term cash flow trend line), not a peak or trough.
2. Construct and value a new trend line scenario based on the company’s 
recent performance. Once again, focus primarily on the long-term trend 
line, because it will have the largest impact on value. Do not worry too 
much about modeling future cyclicality (although future cyclicality will 
be important for financial solvency).
3. Develop the economic rationale for each of the two scenarios, consider-
ing factors such as demand growth, companies entering or exiting the 
industry, and technology changes that will affect the balance of supply 
and demand.
4. Assign probabilities to the scenarios and calculate their weighted values. 
Use the economic rationale and its likelihood to estimate the weights as-
signed to each scenario.
This approach provides an estimate of the value as well as scenarios that put 
boundaries on the valuation. Managers can use these boundaries to improve 
their strategy and respond to signals about which scenario is likely to occur.
Another consideration when valuing cyclical companies in commodity-
linked industries is that starting with revenues may not be the best way to model 
performance. Consider a polyethylene manufacturer, which processes natural 
gas into polyethylene. The traditional approach to valuation would be to model 
sales volumes and polyethylene prices to estimate revenues, from which you