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Risk management for commodity exporting countries: The new role of financial derivatives.

机译:大宗商品出口国的风险管理:金融衍生品的新作用。

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摘要

Commodity price instability has been a permanent concern for developing economies. Vulnerable countries can hedge their revenues using financial derivatives or, under credit constraint conditions, they can smooth revenues with properly designed self-insurance mechanisms such as saving funds. However, the traditional analysis based on expected utility theory has proven to be inadequate to solve the question of intertemporal resource allocation under uncertainty. The reason is that it does not distinguish between risk preferences and tine preferences, and as a consequence, the optimal hedging or saving recommendation becomes biased. We re-examine the optimal risk management strategy for a country with concentrated export revenues in one commodity, using a non-expected utility framework. We find that when solving the representative consumer optimization problem, a utility function that separates risk aversion from intertemporal elasticity becomes extremely relevant particularly when agents face a borrowing constraint.;On the other hand, this work underlines the role that learning can have in reducing market uncertainty. By applying the concept of active learning from system theory, we show that a monopolistic producer facing a dynamic optimization problem under uncertainty, will rather reduce its short term profits, moving away from its static optimal production in order to probe and gain information about the market, obtaining in the process a higher expected profit. We are to able to measure the relative impact that the learning effect for different degrees of risk aversion. We examine the externality that hedging decisions have in terms of speeding up the learning process of market parameters, and identify the elements that enhance this effect. We conclude that as risk aversion increases, the learning impact diminishes, revealing a complementary role between hedging and active learning.;This analysis is later applied through numerical simulations to the specific example of copper in Chile. We therefore also contribute to the discussion of optimal policy responses to reduce external vulnerability of the Chilean economy.
机译:商品价格的不稳定性一直是发展中经济体长期关注的问题。脆弱国家可以使用金融衍生工具对冲收入,或者在信贷约束条件下,可以通过设计合理的自我保险机制(例如节省资金)来平滑收入。然而,基于期望效用理论的传统分析已被证明不足以解决不确定性下的跨期资源分配问题。原因是它不能区分风险偏好和常规偏好,因此,最佳对冲或保存建议会产生偏差。我们使用非预期的效用框架,重新审查针对出口收入集中在一种商品中的国家的最佳风险管理策略。我们发现,当解决代表性的消费者优化问题时,将风险规避与跨期弹性分开的效用函数变得尤为重要,尤其是当代理商面临借款约束时;另一方面,这项工作强调了学习在减少市场中可以发挥的作用。不确定。通过应用系统理论中的主动学习概念,我们表明,在不确定性下面临动态优化问题的垄断生产商宁愿减少其短期利润,而从静态最优生产转向寻找和获取有关市场的信息。 ,从而在过程中获得更高的预期利润。我们能够衡量学习效果对于不同程度的风险规避的相对影响。我们研究了对冲决策在加速市场参数学习过程方面的外部性,并确定了增强这种效果的要素。我们得出的结论是,随着风险规避的增加,学习影响减小,从而揭示了套期保值和主动学习之间的互补作用。该分析随后通过数值模拟应用于智利的铜的特定示例。因此,我们也为减少智利经济外部脆弱性的最佳政策对策的讨论做出了贡献。

著录项

  • 作者

    Cruz, Miguel Jose.;

  • 作者单位

    Stanford University.;

  • 授予单位 Stanford University.;
  • 学科 Finance.;Systems science.
  • 学位 Ph.D.
  • 年度 1996
  • 页码 211 p.
  • 总页数 211
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:49:30

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