投资组合中协方差阵的估计和预测  

Estimation and Prediction of Covariance Matrix in Portfolio

作　　者：刘丽萍[1] LIU Li-ping(School of Mathematics and Statistics,Guizhou University of Finance and Economics,Guiyang 550025,China)

机构地区：[1]贵州财经大学数学与统计学院,贵阳550025

出　　处：《经济研究导刊》2018年第24期92-94,123,共4页Economic Research Guide

基　　金：2016年国家社会科学研究项目(16CTJ013)

摘　　要：为了解除噪声和跳跃以及维数诅咒对协方差阵估计的影响,将修正的门限预平均已实现协方差阵(MTPCOV)与VAR-LASSO模型相结合,估计和预测高维高频数据的协方差阵,并将其应用在投资组合中。研究发现,由VAR-LASSO模型预测的MTPCOV估计量应用在投资组合中,可以使得投资者获得更高的收益,并降低投资风险。In order to solve the influence of noise、jump and dimension curse on covariance matrix estimation,this paper combines the modified threshold pre-averaging covariance matrix（MTPCOV）with VAR-LASSO model,to estimate and predict the covariance matrix of high-dimensional and high-frequency data.The main finding is：The MTPCOV which is predicted by the VAR-LASSO model can be used in the portfolio to gain higher profits and reduce investment risk.

关 键 词：金融协方差阵 MTPCOV估计量 VAR-LASSO模型 

分 类 号：F830.9[经济管理—金融学]