  The real options approach is now considered an effective alternative to the
corporate DCF model for a feasibility study. The current paper offers a
practical methodology employing binomial trees and real options techniques for
evaluating investment projects. A general computation procedure is suggested
for the decision tree with two active stages of real options, which correspond
to additional investments. The suggested technique can be used for most real
options, which are practically essential regarding enterprise strategy. The
special case named Binomial-Random-Cash-Flow Real Options Model with random
outcomes is developed as the next step of real options modelling. Project Value
at Risk is introduced and used as a criterion of investment project feasibility
under the assumption regarding random outcomes. In particular, the Gaussian
probability distribution is used for modelling option outcomes uncertainty. The
choice of the Gaussian distribution is caused by the desire to obtain estimates
in the final analytical form. Choosing another distribution for random outcomes
leads to using Monte Carlo simulation, for which a general framework is
developed by demonstrating some instances. The author could avoid the
computational complexity that makes these solutions feasible for business
practice.
