scholarly journals A dynamic component model for forecasting high-dimensional realized covariance matrices

2017 ◽  
Vol 1 ◽  
pp. 40-61 ◽  
Author(s):  
Luc Bauwens ◽  
Manuela Braione ◽  
Giuseppe Storti
Keyword(s):  
Covariance Matrices ◽  
Component Model ◽  
High Dimensional ◽  
Dynamic Component ◽  
Realized Covariance

scholarly journals Multivariate Fractional Components Analysis

2021 ◽  
Author(s):  
Tobias Hartl ◽  
Roland Jucknewitz
Keyword(s):  
Time Series ◽  
Long Memory ◽  
Covariance Matrices ◽  
High Dimensional ◽  
Nonstationary Processes ◽  
Realized Covariance ◽  
Out Of Sample ◽  
Short Memory ◽  
Components Analysis ◽  
Fractional Orders

Abstract We propose a setup for fractionally cointegrated time series which is formulated in terms of latent integrated and short-memory components. It accommodates nonstationary processes with different fractional orders and cointegration of different strengths and is applicable in high-dimensional settings. In an application to realized covariance matrices, we find that orthogonal short- and long-memory components provide a reasonable fit and competitive out-of-sample performance compared with several competing methods.

Global one-sample tests for high-dimensional covariance matrices

2021 ◽  
pp. 1-23
Author(s):  
Xiaoyi Wang ◽  
Baisen Liu ◽  
Ning-Zhong Shi ◽  
Guo-Liang Tian ◽  
Shurong Zheng
Keyword(s):  
Covariance Matrices ◽  
High Dimensional
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