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Having developed a general valuation framework that combines Bayesian updating with real options analysis in the previous chapter, this chapter aims at analyzing the model and deriving properties in closed form.We will hereby study 1) how the project value changes if the uncertainty is reduced through an information update, 2) under which conditions it will be most beneficial to conduct an update, and 3), how the underlying cost structure influences the derived results. For the derivation of these properties it is insightful to maintain the distinction between the two perspectives (ex ante and ex post) as discussed in the previous chapter. We will start with an analysis of the corresponding properties of an information update once the signal is observed and hence, known. These results can then be applied to the analysis of the actual point of interest, namely model properties in expectation of a later information update.
KeywordsModel Property Identical Project Uncertainty Reduction Market Requirement Prior Variance
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