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Production and Hedging Under Smooth Ambiguity Preferences

机译:平滑歧义偏好下的生产和对冲

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摘要

This paper examines the optimal production and hedging decisions of the competitive firm facing ambiguous price and background risk. Ambiguity is modeled by a second-order probability distribution that captures the firm's uncertainty about which of the subjective beliefs govern the price and background risk. Ambiguity preferences are modeled by the (second-order) expectation of a concave transformation of the (first-order) expected utility of profit conditional on each plausible subjective joint distribution of the price and background risk. When the background risk is additive in nature, we show that the separation theorem holds in that the firm's optimal production decision depends neither on the firm's attitude toward ambiguity nor on the incident of the underlying ambiguity. We derive necessary and sufficient conditions under which the firm's optimal forward position is completely characterized. When the background risk is multiplicative in nature, we derive sufficient conditions under which the firm reduces its optimal output level and opts for an under-hedge. Contrary to the conventional wisdom, we show that the behavior of the firm is affected by the introduction of ambiguity even when the firm is ambiguity neutral. (c) 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:506-518, 2016
机译:本文研究了面临不确定的价格和背景风险的竞争企业的最优生产和对冲决策。模糊度是通过二阶概率分布来建模的,该分布捕获了公司关于哪个主观信念控制价格和背景风险的不确定性。歧义偏好通过对价格和背景风险的每个合理的主观联合分布条件的(一阶)预期利润效用的凹变换的(二阶)期望进行建模。当背景风险本质上是累加的时,我们证明了分离定理成立,即企业的最优生产决策既不依赖于企业对歧义的态度也不依赖于潜在歧义的发生。我们得出了必要的和充分的条件,可以在此条件下完全表征公司的最佳远期头寸。当背景风险本质上是可乘的时,我们得出充分条件,在此条件下企业降低其最佳产出水平并选择了对冲措施。与传统观点相反,我们表明,即使公司是中立的,公司的行为也会受到歧义的引入的影响。 (c)2015 Wiley Periodicals,Inc.Jrl Fut Mark 36:506-518,2016年

著录项

  • 来源
    《Journal of futures markets》 |2016年第5期|506-518|共13页
  • 作者

    Wong Kit Pong;

  • 作者单位

    Univ Hong Kong, Finance, Hong Kong, Hong Kong, Peoples R China|Univ Hong Kong, Sch Econ & Finance, Pokfulam Rd, Hong Kong, Hong Kong, Peoples R China;

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  • 正文语种 eng
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