Real options in the forest: what if prices are mean-reverting?

Gjølberg, Ole; Guttormsen, Atle G.

doi:10.1016/s1389-9341(01)00076-4

Cited by 47 publications

(19 citation statements)

References 25 publications

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“…6, stochastic dynamic programming (SDP) was the most common technical tool used to deal with risk in forestry. The studies are closely related to the real options literature as shown by Plantinga (1998) and with examples like Thorsen (1999a, b), Abildtrup and Strange (1999), Duku-Kaakyire and Nanang (2004), Gjolberg and Guttormsen (2002) and many others. To a large extent, this group of studies correlates with the literature considering uncertainty in terms of the stochastic evolution of future prices (Brazee and Mendelsohn 1988;Thomson 1992;Gong 1994;Yoshimoto and Shoji 1998;Gong et al 2005), present value measures (Norstrøm 1975;McCarthy et al 2001;Abildtrup and Strange 1999;Malchow-Møller et al 2004), stochastic interest rates Koskela 2001, 2003;Buongiorno and Zhou 2011) and similar, but not exclusively.…”

Section: Operations Research Methodsmentioning

confidence: 64%

“…The field is closely related to the real options literature as shown by Plantinga (1998) and with examples like, e.g. Thorsen (1999a, b), Abildtrup and Strange (1999), Duku-Kaakyire and Nanang (2004), Gjolberg and Guttormsen (2002) and many others. The main limitation but also advantage of these types of studies is that they usually apply empirically based models to predict forest development or development in prices over time (e.g.…”

Section: Conclusion With a Focus On Future Research Needsmentioning

confidence: 83%

“…Plantinga 1998;Gong 1999;Gjolberg and Guttormsen 2002) and vector AP (VAP), e.g. Gong and Yin (2004) and Jacobsen and Helles (2006).…”

Section: Models Of Risk Analysismentioning

confidence: 99%

See 2 more Smart Citations

A review of decision-making approaches to handle uncertainty and risk in adaptive forest management under climate change

Yousefpour

Jacobsen

Thorsen

et al. 2011

Annals of Forest Science

182

141

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Abstract• Context This review paper provides an overview of approaches to which we may resort for handling the complex decision problems involving uncertainty and risk that climate change implies for forest managers. Modelling approaches that could support adaptive management strategies seem to be called for, not only as climate change denotes increased economic uncertainty but also because new and more reliable information becomes available as time passes and climate changes.• Aims The paper (1) provides a broad overview of state-ofthe-art methods for optimal decision making under risk and uncertainty in forestry and (2) elaborates on the possible use of these methods in adaptive forest management under climate change.

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Section: Operations Research Methodsmentioning

confidence: 64%

Section: Conclusion With a Focus On Future Research Needsmentioning

confidence: 83%

See 1 more Smart Citation

A review of decision-making approaches to handle uncertainty and risk in adaptive forest management under climate change

Yousefpour

Jacobsen

Thorsen

et al. 2011

Annals of Forest Science

182

141

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“…Yin [29] discusses harvest timing, land acquisition, and entry decisions combining forest level analysis and options valuation approach. Other authors have studied the impact of assuming that stochastic prices follow a mean reverting process rather than geometric brownian motion, see e.g., [16] and [13].…”

Section: Literature Reviewmentioning

confidence: 99%

A Stochastic Dynamic Programming Model for Valuing a Eucalyptus Investment

Cunha

Fontes

2008

Springer Optimization and Its Applications

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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 re-plantation, 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, since 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 present practice of forest managers and allow for considerable gains.

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“…For example, Insley (2002) investigates the role of the timber price process on the rotation length in a single-rotation model, while Insley and Rollins (2005) solve for the optimal harvest policy when multiple rotations are allowed. Gjolberg and Guttormsen (2002) study the tree-cutting problem under the assumption of mean-reverting (rather than random-walk) stumpage prices, and Alvarez (2004) examines the role of timber price volatility on harvest policy and forest values. However, none of these papers consider the effect of carbon subsidies or taxes.…”

Section: Introductionmentioning

confidence: 99%