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中文摘要：
本文分别在正态分布和任意分布设定下讨论最小在险价值（VaR）的风险对冲问题。在正态分布设定下，本文深入讨论最小方差对冲比率和最小VaR对冲比率的性质，并得出最小VaR对冲策略下组合收益率的均值和方差大于最小方差策略下组合收益率的均值和方差。在任意分布设定下，本文构建一种新的VaR对冲模型，该模型引入非参数核估计方法对VaR进行估计，然后基于VaR核估计量建立风险对冲问题，实现风险估计与风险对冲同步进行。实证结果非常稳健地表明，不做任何分布假设下的核估计法得到的风险对冲效果优于最小方差对冲策略和正态分布设定下的最小VaR对冲策略。
英文摘要：
In this paper, we research the risk hedging strategies based on Value-at-Risk under normal distribution and arbitrary distribution settings respectively. Under the assumption of normal distribution, this paper discusses the properties of the hedge ratio of minimum variance strategy and minimum VaR strategy thoroughly and find that the mean and variance of portfolio return induced by minimum VaR strategy are smaller than minimum variance strategy. Without any distribution assumption, this paper constructs a new VaR hedging model which firstly esti- mates VaR by nonparametric kernel estimation method and then embeds the VaR kernel estimator into minimum VaR fomula. By this way, we achieve the goal that risk estimation and risk hedging are implemented simultane- ously. The empirical results are very robust to show that the kernel estimation method can reduce risk more effec- tively than minimum variance strategy and minimum VaR strategy under normal distribution setting.
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