主讲人简介：

龚玉婷老师现为经济金融系副教授。本科和硕士毕业于上海财经大学，博士毕业于上海交通大学。主要研究方向为金融计量，包括连接函数、混频数据抽样模型、区制转换模型、债券定价。以第一作者或通讯作者身份在国内外权威期刊发表多篇文章，包括Journal of Financial Econometrics、Transportation Research Part E。主持国家自然科学基金面上项目1项、国家自然科学基金青年项目1项。同时担任Journal of Economic Dynamics and Control、International Review of Economics & Finance、Economic Modelling、Finance Research Letters、经济学（季刊）、系统工程理论与实践等国内外10余种领域权威期刊的匿名审稿人。

内容提要：

The relationship between foreign exchange markets is an important issue for portfolio selection and risk management. Understanding the economic factors affecting the interaction between foreign exchanges allows investors to improve their portfolio performance. This paper proposes a mixed frequency data sampling copula model with explanatory variables (copula-MIDAS) that incorporates low frequency explanatory variables into a high frequency dynamic copula model. The new model enables us to investigate the impacts of economic factors on the relationship between foreign exchanges markets, regardless of their marginal distributions. In an application to Canadian dollars, British pounds and Japanese yen, we find that the pairwise dependence of these currencies against US dollars is influenced by their output gap, inflation gap and interest rate gap. In particular, the impact of output gap on the cross-market dependence is much longer than the impact of inflation and interest rate gap.