论文标题：A Factor-Based Estimation of Integrated Covariance Matrix with Noisy

　　发表时间：2020.12 Accepted

　　论文所有作者：Yucheng Sun and Wen Xu

　　期刊名及所属分类：Journal of Business & Economic Statistics(国际A)

　　英文摘要：This article studies a high-dimensional factor model with sparse idiosyncratic covariance matrix in continuous time, using asynchronous high-frequency financial data contaminated by microstructure noise. We focus on consistent estimations of the number of common factors, the integrated covariance matrix and its inverse, based on the flat-top realized kernels introduced by Varneskov. Simulation results illustrate the satisfactory performance of our estimators in finite samples. We apply our methodology to the high-frequency price data on a large number of stocks traded in Shanghai and Shenzhen stock exchanges, and demonstrate its value for capturing time-varying covariations and portfolio allocation.

　　中文摘要：本文利用受微观结构噪声污染的异步高频金融数据，研究了连续时间条件下具有稀疏特质协方差矩阵的高维因子模型。本文主要研究基于Varneskov引入的平顶实现核的公因数、整协方差矩阵及其逆的一致估计。仿真结果表明，该估计器在有限样本条件下具有良好的性能。本文将该方法应用于沪深两市的大量股票高频价格数据，验证了该方法对获取时变协变量和投资组合配置的价值。