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Implementing the conditional value at risk approach for even-flow forest management planning

机译:为均匀流森林管理规划实施有条件的风险价值方法

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Deciding on a plan of action for a forest holding involves a significant amount of uncertainty. As forest planning involves the use and extraction of resources, uncertainty lies in both the future development of the forest (biological uncertainty) and the development of the market for forest-based products (economic uncertainty). Additionally, natural hazards can be a source of unexpected losses. In traditional forest management planning, the most common way to deal with uncertainty is to ignore it. Growth models are used that are assumed to be correct, and timber prices are assumed to be held constant. By ignoring the fact that these models provide only one representation of what may happen, the forest owner may get an overly optimistic (or pessimistic) view of the potential value of the forest holding. Through a stochastic programming formulation, these uncertainties can be modelled directly into the optimization formulation, and a management plan can be created that incorporates the risk preferences of the decisionmaker. This is highlighted through an example that maximizes the net present value of the holding while minimizing the conditional value at risk of obtaining a stated even flow of income.
机译:决定森林经营权的行动计划涉及大量不确定性。由于森林规划涉及资源的利用和提取,因此不确定性既存在于森林的未来发展中(生物不确定性),也取决于森林产品市场的发展(经济不确定性)。此外,自然灾害可能是意外损失的来源。在传统的森林经营规划中,处理不确定性的最常见方法是忽略它。假定使用的增长模型是正确的,并且假定木材价格保持不变。通过忽略这些模型仅提供可能发生情况的一种表示这一事实,森林所有者可能对森林所有权的潜在价值过于乐观(或悲观)。通过随机规划公式,可以将这些不确定性直接建模到优化公式中,并可以创建包含决策者风险偏好的管理计划。这是通过一个示例来突出显示的,该示例使所持股份的净现值最大化,而使有可能获得规定的收入流风险的条件值最小化。

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