报告题目：基于经验似然的金融时间序列的VaR和 ES估计
报告人：浙江大学数学科学学院张奕教授
报告内容：
We construct a specific form of piecewise distortion function which can distort a random risk to its expectile and define a class of expectile distortion measure which is generated from the piecewise form distortion. The consistent estimation of the expectile distortion parameter is given by the maximum empirical likelihood method. As the application, we discuss a new premium principle based on the expectile distortion measure.
We propose a new method for estimating conditional Value-at-risk (VaR) and expected shortfall (ES) of financial time series, which based on the combination of composite expectile and empirical likelihood. The method of composite expectile is used to estimate the conditional variance of conditional heteroscedasticity model such as GARCH.
报告人简介：
张奕，浙江大学数学系教授，博士生导师。主要从事保险精算，统计大样本，计量经济研究，先后发表高水平论文50多篇，主持国家自然科学基金面上项目、国家社科基金多项。
报告时间：2018年5月21日下午14:00-15:00
报告地点：9教330教室
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