学术报告
报告题目：High Dimensional and Dynamic Covariance MatrixEstimation with an Application to Portfolio Allocation
报 告 人：郭绍俊助理研究员
中国科学院数学与系统科学研究院
时 间：2015年12月24日(星期四)下午15:30
地 点：统计研究院426教室（原附中计算机与控制工程学院办公楼四楼东侧)
摘 要:Estimation of high dimensional covariance matrices is an interesting and important research topic. In this talk, we propose a dynamic structure and develop an estimation procedure for high dimensional covariance matrices. Asymptotic properties are derived to justify the estimation procedure and simulation studies are conducted to demonstrate its performance when the sample size is finite. By exploring a financial application, an empirical study shows that portfolio allocation based on dynamic high dimensional covariance matrices can significantly outperform the market from 1995 to 2014. Our proposed method also outperforms portfolio allocation based on the sample covariance matrix, the factor model given in Fan, Fan and Lv (2008), and the shrinkage estimator given in Ledoit and Wolf (2004). This is joint work with John Box and Wenyang Zhang
统计研究院
2015年12月24日