This work presents the application of the Monte Carlo Simulation method
and the Decision Tree Analysis approach when dealing with the economic
valuation of projects which are subjected to risks and uncertainties.
The Net Present Value of a project is usually used as an investment
decision parameter. Using deterministic models to calculate a project's
Net Present Value neglects the risky and uncertain nature of real life
projects and consequently leads to useless valuation results. Realistic
valuation models need to use probability density distributions for the
input parameters and certain probabilities for the occurrence of
specific events during the life time of a project in combination with
the Monte Carlo Simulation method and the Decision Tree Analysis
approach. After a short introduction a brief explanation of the
traditional project valuation methods is given. The main focus of this
work lies in using the Net Present Value method as a basic valuation
tool in conjunction with the Monte Carlo Simulation technique and the
Decision Tree Analysis approach to form a comprehensive method for
project valuation under risk and uncertainty. The extensive project
valuation methodology introduced is applied on two fictional projects,
one from the pharmaceutical sector and one from the oil and gas
exploration and production industry. Both industries deal with high
risks, high uncertainties and high costs, but also high rewards. The
example from the pharmaceutical industry illustrates very well how the
application of the Monte Carlo Simulation and Decision Tree Analysis
method, results in a well-diversified portfolio of new drugs with the
highest reward at minimum possible risk. Applying the presented
probabilistic project valuation approach on the oil exploration and
production project shows how to reduce the risk of losing big.