摘要/Abstract

套期保值的模型众多，其适用性也较为广泛，唯独Copula函数在刻画多元变量的联合分布方面表现的最为出色。对于多元金融时间序列之间复杂的动态相关性，传统的统计模型常常表现的较为乏力，Copula函数的登台恰逢其时，此函数不仅能分解多元变量的联合分布，将其化为各变量的累积边缘分布函数跟一个特定的Copula函数，还能灵活精准的描述多元变量之间的相依结构。故Copula函数在金融研究领域的应用越来越广泛。笔者首先阐述了套期保值率有关的理论基础，并由此引出动态Copula模型，用它来估计沪深300股指期货的套期保

There are a lot of hedge model, its applicability is also more widespread, the most outstanding exception Copula function in multivariate joint distribution portray aspects of performance. For complex dynamic correlation between the traditional multivariate statistical models of financial time series often show relatively weak, there Copula function of the right time, this function can not only decompose multivariate joint distribution, and be translated into each variable the cumulative distribution function of the edge Copula with a specific function, but also flexible and precise description of multivariate dependence structure between. So Copula function in the field of financial research more widely.The author first describes the theoretical basis for the relevant hedging rate, and thus leads to a dynamic Copula model and use it to estimate the CSI 300 stock index futures hedge ratio, and then compared with the traditional hedging model. Empirical estimation results show that the effect of hedging the best Copula model, which is more price risk aversion function, OLS model is followed.at the same time,in Copula model family, T-Copula function hedging best, N-Copula function slightly less.