Kheyri, AzamBekker, Andriette, 1958-Arashi, Mohammad2023-09-072023-09-072022-11-12Kheyri, A.; Bekker, A.; Arashi, M. High-Dimensional Precision Matrix Estimation through GSOS with Application in the Foreign Exchange Market. Mathematics 2022, 10, 4232. https://DOI.org/10.3390/math10224232.2227-739010.3390/math10224232http://hdl.handle.net/2263/92241DATA AVAILABILITY STATEMENT : The data under consideration in this study is in the public domain.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.en© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.Exchange rateGaussian graphical modelGraphical elastic netHigh-penalized log-likelihoodPrecision matrix estimationRidge estimationSDG-08: Decent work and economic growthArticle