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[6月4日] 计量金融与大数据分析workshop

发布日期:2021-05-31 11:09    来源:


主讲人:蔡宗武教授(Zongwu Cai, Department of Economics, University of Kansas)

题目:动态金融网络的半参数建模(Semiparametric Modeling for Dynamic Financial Networks)

时间:2021年6月4日(周五)10:00 AM -- 11:30 AM

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主题:Zoom meeting invitation - 计量金融大数据分析workshop的 Zoom 会议

时间:2021年6月4日 09:30 上午 北京,上海

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会议号:663 3371 5453



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会议号:663 3371 5453



报告摘要:The degree of interdependences among holdings of financial sectors and its varying patterns are key in forming systemic risks within a financial system. In this article, we propose a VAR model of conditional quantiles with functional coefficients to construct a novel class of dynamic network system, of which the interdependences among tail risks such as Value-at-Risk are allowed to vary with a variable of general economy. Methodologically, we develop an easy-to-implement two-stage procedure to estimate functionals in the dynamic network system by the local linear smoothing technique. We establish the consistency and the asymptotic normality of the proposed estimator under time series settings. The simulation studies are conducted to show that our new methods work fairly well. The potential of the proposed estimation procedures is demonstrated by an empirical study of constructing and estimating a new type of dynamic financial network. This is a joint work with Mr. Xiyuan Liu and it can be downloaded at the RePec web site at


Dr. Zongwu Cai is the Charles Oswald Professor of Econometrics and a Professor of Economics at Department of Economics, The University of Kansas. His research interests include econometrics, quantitative finance, risk management, data-analytic modeling, nonlinear and nonstationary time series, and their applications, and among others. His primary research focuses on developing and justifying econometric methodology and applications in economics and finance. His work has been published extensively in professional journals, including both leading econometrics and statistics journals: Journal of Econometrics, Econometric Theory, The Journal of American Statistical Association, and more.