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.

Pharmaceutical and Biomedical Portfolio Management in a Changing Global Environment explores some of the critical forces at work today in the complex endeavour of pharmaceutical and medical product development. Written by experienced professionals, and including real-world approaches and best practice examples, this new title addresses three key areas – small molecules, large molecules, and medical devices - and provides hard-to-find, consolidated information relevant to and needed by pharmaceutical, biotech, and medical device company managers.

Helping you become a creative, logical thinker and skillful "simulator," Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies provides broad coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization. It presents the theories and metho

We are pleased to welcome readers to this issue of the Journal of Applied Operational Research (JAOR), Volume 5, Number 3. The journal reports on developments in all aspects of operational research, including the latest advances and applications. It is a primarily goal of the journal to focus on and publish practical case studies which illustrate real-life applications.

Monte Carlo methods have been used for decades in physics, engineering, statistics, and other fields. Monte Carlo Simulation and Finance explains the nuts and bolts of this essential technique used to value derivatives and other securities. Author and educator Don McLeish examines this fundamental process, and discusses important issues, including specialized problems in finance that Monte Carlo and Quasi-Monte Carlo methods can help solve and the different ways Monte Carlo methods can be improved upon. This state-of-the-art book on Monte Carlo simulation methods is ideal for finance professionals and students. Order your copy today.