A Stochastic Dynamic Programming Model for Valuing a Eucalyptus Investment

Part of the Springer Optimization and Its Applications book series (SOIA, volume 25)


This work proposes an exercise-dependent real options model for the valuation and optimal harvest timing of a forestry investment in eucalyptus. Investment in eucalyptus is complex, as trees allow for two cuts without replantation and have a specific time and growth window in which they are suitable for industrial processing into paper pulp. Thus, path dependency in the cutting options is observed, as the moment of exercise of the first option determines the time interval in which the second option may be exercised. Therefore, the value of the second option depends on the history of the state variables rather than on its final value. In addition, the options to abandon the project or convert land to another use, are also considered. The option value is estimated by solving a stochastic dynamic programming model. Results are reported for a case study in the Portuguese eucalyptus forest, which show that price uncertainty postpones the optimal cutting decisions. Moreover, optimal harvesting policies deviate from current practice of forest managers and allow for considerable gains.


Cash Flow Real Option Paper Pulp Extended Problem Geometric Brownian Motion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank FCT for the financial support through scholarship BD/12610/03 and project POCI/MAT/61842/04.


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© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Universidade Católica Portuguesa and Lancaster UniversityFaculdade de Economia e GestãoPortoPortugal

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