论文标题
在模型歧义下的成本效益收益
Cost-efficient Payoffs under Model Ambiguity
论文作者
论文摘要
Dybvig（1988a，b）在一个完整的市场中解决了一个问题，即找到达到给定目标分布最便宜的回报（“成本效益的回报”）。但是，在歧义的情况下，回报的分布不再确定。我们研究了找到最便宜的收益的问题，其最差的案例分配随机地主导了给定的目标分布（“稳健的成本效益回报”）并在某些条件下确定解决方案。我们研究了Gilboa和Schmeidler的“强大的成本效率”与Maxmin预期的实用程序设置之间的联系，以及在可能非预期的效用设置中具有强大的偏好之间的联系。具体而言，我们表明，Maxmin强大的预期实用程序的解决方案必然具有良好的成本效益。我们用涉及在风险资产的漂移和波动性上的不确定性的例子来说明我们的研究。
Dybvig (1988a,b) solves in a complete market setting the problem of finding a payoff that is cheapest possible in reaching a given target distribution ("cost-efficient payoff"). In the presence of ambiguity, the distribution of a payoff is, however, no longer known with certainty. We study the problem of finding the cheapest possible payoff whose worst-case distribution stochastically dominates a given target distribution ("robust cost-efficient payoff") and determine solutions under certain conditions. We study the link between "robust cost-efficiency" and the maxmin expected utility setting of Gilboa and Schmeidler, as well as more generally with robust preferences in a possibly non-expected utility setting. Specifically, we show that solutions to maxmin robust expected utility are necessarily robust cost-efficient. We illustrate our study with examples involving uncertainty both on the drift and on the volatility of the risky asset.
