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  <title>Project valuation and decision making under risk a</title>
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 <genre authority="marcgt">bibliography</genre>
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  <place>
   <placeTerm type="text">Norderstedt</placeTerm>
   <publisher>Books on Demand</publisher>
   <dateIssued>2015</dateIssued>
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  <extent>xiii, 93 p. : figs., tabs. ; 21 cm.</extent>
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 <note>&lt;br&gt;&lt;br&gt;&lt;br&gt;This work presents the application of the Monte Carlo Simulation method &#13;
and the Decision Tree Analysis approach when dealing with the economic &#13;
valuation of projects which are subjected to risks and uncertainties. &#13;
The Net Present Value of a project is usually used as an investment &#13;
decision parameter. Using deterministic models to calculate a project's &#13;
Net Present Value neglects the risky and uncertain nature of real life &#13;
projects and consequently leads to useless valuation results. Realistic &#13;
valuation models need to use probability density distributions for the &#13;
input parameters and certain probabilities for the occurrence of &#13;
specific events during the life time of a project in combination with &#13;
the Monte Carlo Simulation method and the Decision Tree Analysis &#13;
approach. After a short introduction a brief explanation of the &#13;
traditional project valuation methods is given. The main focus of this &#13;
work lies in using the Net Present Value method as a basic valuation &#13;
tool in conjunction with the Monte Carlo Simulation technique and the &#13;
Decision Tree Analysis approach to form a comprehensive method for &#13;
project valuation under risk and uncertainty. The extensive project &#13;
valuation methodology introduced is applied on two fictional projects, &#13;
one from the pharmaceutical sector and one from the oil and gas &#13;
exploration and production industry. Both industries deal with high &#13;
risks, high uncertainties and high costs, but also high rewards. The &#13;
example from the pharmaceutical industry illustrates very well how the &#13;
application of the Monte Carlo Simulation and Decision Tree Analysis &#13;
method, results in a well-diversified portfolio of new drugs with the &#13;
highest reward at minimum possible risk. Applying the presented &#13;
probabilistic project valuation approach on the oil exploration and &#13;
production project shows how to reduce the risk of losing big.&lt;br&gt;</note>
 <note type="statement of responsibility"></note>
 <classification>ELAV/AEC</classification>
 <identifier type="isbn">9783734755439</identifier>
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