No abstract

No abstract

The remediation of contaminated sites is often subject to substantial cost overruns. This persistent discrepancy between estimated and realized costs is chiefly responsible for misguided land use and wasteful delays in the reconversion of former industrial sites. In order to deal with incomplete information and uncertainty in this context, this paper draws on stochastic modelling and mathematical finance methods. We show that relatively simple and usable formulas can then be derived for better assessing cleanup strategies. These formulas apply to generic remediation technologies and scenarios. They are robust to misspecification of key parameters (like the effectiveness of a prescribed treatment). They also yield practical rules for decision making and budget provisioning.

We study the perpetual American option characteristics in the case where the underlying dynamics involve a Brownian motion and a point process with a stochastic intensity. No assumption on the distribution of the jump size is made and we work with an arbitrary positive or negative jump. After proving the existence of an optimal stopping time for the problem and characterizing it as the hitting time of an optimal boundary,we provide closed-form formulae for the option value, as well as for the Laplace transform of the optimal stopping time. These results are then applied to the analysis of a real option problem when considering the impact of a fundamental and brutal change in the investment project environment. The consequences of this impact, that can seriously modify, positively or negatively, the project's future cash flows and therefore the investment decision, are illustrated numerically via the study of some examples. Mathematics Subject Classification (2000): 60 G 40 ; 60 G 55 ; 60K99 ; 91 B 28

No abstract