Any valuation involving future value will include a forecast period. These vary widely by industry. With the average life spans of companies shrinking, 10 years seems to be the maximum.  Such a time horizon is used in the pharmaceutical industry, because it takes many years to develop drugs and then obtain approval for them.

By contrast, in the field of information technology, a three-year horizon is typical. In the subfield of artificial intelligence (including deep learning, machine learning, natural language processing, and quantum computing) the window may be just a matter of months. Urgency on the part of a buyer or seller will tend to increase or decrease deal price, respectively. The presence of competitive bids will also tend to raise deal price.  

This is where a few financial skills can really help a dealmaker. One of the benefits of “sensitivity analysis” is to discover the effects of different time horizons and hurdle rates on a target company’s present value.

During volatile times dealmakers tend to shorten their forecast period and increase their hurdle rates just because conditions are uncertain—even when the uncertainties they face are not random. (One might say that they are known unknowns.) This shortening and/or increase is a poor substitute for factoring in quantifiable risk. In many cases, with a little work, the uncertainties can be converted to probabilities.