摘要
石油市场和股票市场作为现代经济中两个重要的市场,在经济活动中发挥着重要的作用。二者之间的关系对研究市场间的价格波动和风险传递有着重要的意义,本文通过vinecopula模型对国际油价和中美两国股价之间相依关系进行分析,并将得到的相依关系运用到风险管理中。利用国际油价和中美各十个行业股票价格指数进行相依关系建模,得到相应的相依结构和相依关系,选择出与油价相依关系较强的行业股票价格指数和油价构建投资组合,利用相依关系模拟出收益率数据,度量投资组合的风险。实证研究结果表明中美两国的行业股票价格指数与国际油价的相依关系存在着显著的不同,中国行业股票价格指数与国际油价之间的相依关系要弱于美国行业股票价格指数与国际油价的相依关系;同时利用相依关系组成投资组合,对两组投资组合进行风险度量,风险度量的结果显示vine copula--GARCH能对具有较强的相依关系的变量组成的投资组合风险有很好的估计。
The oil market and stock market are the important part of modern economy, playing an important role in the economy. The relationship between these markets plays a key role in analyzing the fluctuation of price and risk transmission. The vine copula model is used in this paper to research the dependence relationship is used among the oil price, Chinese stock price and American stock price, and then the dependence relationship to manage risk. The vine copula model is used to model the dependence relationship of the oil price and ten industrial stock prices in China and American respectively, therefore the dependence relationship and dependence structure is estimated. And then oil price and the industrial stock price that has stronger dependence relationship with oil price are selected to construct the portfolio and meantime measure the risk of portfolio. The research findings of this paper show the dependence relationships of oil price, Chinese and American stock prices are different in industry, the dependence relationship between China stock price and oil price is weaker than the dependence relationship between American stock price and oil price. At the same time, dependence relationships are also used to establish two portfolios and estimate their risk, empirical results find that the vine copula model has a better performance in estimating the risk of portfolio which is established by stronger dependence relationship. The research will expand the application of the vine copula model and the risk measurement using vine copula.
作者
余乐安
查锐
贺凯健
汤铃
YU Le-an;ZHA Rui;HE Kai-jian;TANG Ling(School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China;School of Business, H unan University of Science and Technology, Xiangtan 411201, China;School of Economics and Management, Beihang University, Beijing 100191, China)
出处
《中国管理科学》
CSSCI
CSCD
北大核心
2018年第11期74-82,共9页
Chinese Journal of Management Science
基金
国家自然科学基金重点资助项目(71433001)
