Example 1. A platform investment in R&D is a typical example where DTA can be used. It is graphically explained in Figure 2.3. The numbers on the right next to the final point (denoted with ct) give the NPVs at the end of year 3 in the respective market stage of the expected discounted cash flows of the years 3 and 4 - 10. It is assumed that at the end of year 10, the last year of production within the project, the plant is closed down at no cost. The cash flows are assumed to occur at the end of the respective year, although the investments have to be made at the beginning of that year.
The remaining calculations are the same as in example 1. They produce the decision tree of Figure 2.4 in the case of an option to abandon for a salvage value in this example of a platform investment in R&D. It finally yields an NPV of 1 043, so that the investment would be undertaken. This NPV is called a strategic NPV since it includes a real option. The NPV of −32 previously calculated in the absence of a real option is called static NPV. The value of the real option can therefore be calculated as:
In summary, DTA is well suited to price some types of real options. It can price sequential investment decisions in which management decisions are made at discrete points in the future and uncertainty is resolved at discrete points in time as well. DTA is able to handle this embedded flexibility but the practical application has serious limitations: the number of discrete points in time can get large, thus, creating an extremely complex tree. Trigeorgis refers to this as decision-bush analysis47 instead of decision-tree analysis. Realistic corporate budgeting situations cannot be properly handled that way. Second, the applied discount rate poses a problem since it is usually assumed to be constant. So, when uncertainty gets resolved at decision nodes, the DTA method does not use a changed discount factor. DTA cannot therefore reflect this change in the riskiness of the project expressed in the discount rate