CVaR风险度量模型在投资组合中的运用

An Application of CVaR Models in the Portfolio

风险价值(VaR)是近年来金融机构广泛运用的风险度量指标,条件风险价值(CVaR)是VaR的修正模型,也称为平均超额损失或者尾部VaR,它比VaR具有更好的性质。在本文中,我们将运用风险度量指标VaR和CVaR,提出一个新的最优投资组合模型。介绍了模型的算法,而且利用我国的股票市场进行了实证分析,验证了新模型的有效性,为制定合理的投资组合提供了一种新思路。

Value-at-Risk (VaR) is a widely used risk measure index by financial institution in recent years. Conditional Value-at-Risk (CVaR) is the revised model of VaR, also called Mean Excess Loss or Tail VaR with better properties. In this paper, we'll put forward a new optimal portfolio model by using risk measure index VaR and CVaR. We introduce the algorithm of our model and a case study for our stock market is performed to demonstrate how the new optimization techniques can be implemented. It provides a new idea for establishing a rational portfolio.