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High-Dimensional Precision Matrix Estimation through GSOS with Application in the Foreign Exchange Market.
- Source :
-
Mathematics (2227-7390) . Nov2022, Vol. 10 Issue 22, p4232. 19p. - Publication Year :
- 2022
-
Abstract
- This article studies the estimation of the precision matrix of a high-dimensional Gaussian network. We investigate the graphical selector operator with shrinkage, GSOS for short, to maximize a penalized likelihood function where the elastic net-type penalty is considered as a combination of a norm-one penalty and a targeted Frobenius norm penalty. Numerical illustrations demonstrate that our proposed methodology is a competitive candidate for high-dimensional precision matrix estimation compared to some existing alternatives. We demonstrate the relevance and efficiency of GSOS using a foreign exchange markets dataset and estimate dependency networks for 32 different currencies from 2018 to 2021. [ABSTRACT FROM AUTHOR]
- Subjects :
- *FOREIGN exchange market
*HIGH-dimensional model representation
Subjects
Details
- Language :
- English
- ISSN :
- 22277390
- Volume :
- 10
- Issue :
- 22
- Database :
- Academic Search Index
- Journal :
- Mathematics (2227-7390)
- Publication Type :
- Academic Journal
- Accession number :
- 160463950
- Full Text :
- https://doi.org/10.3390/math10224232