Sparse precision matrices for minimum variance portfolios

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F19%3A10242950" target="_blank" >RIV/61989100:27510/19:10242950 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007%2Fs10287-019-00344-6" target="_blank" >https://link.springer.com/article/10.1007%2Fs10287-019-00344-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10287-019-00344-6" target="_blank" >10.1007/s10287-019-00344-6</a>

Result language
angličtina
Original language name
Sparse precision matrices for minimum variance portfolios
Original language description
Financial crises are typically characterized by highly positively correlated asset returns due to the simultaneous distress on almost all securities, high volatilities and the presence of extreme returns. In the aftermath of the 2008 crisis, investors were prompted even further to look for portfolios that minimize risk and can better deal with estimation error in the inputs of the asset allocation models. The minimum variance portfolio a la Markowitz is considered the reference model for risk minimization in equity markets, due to its simplicity in the optimization as well as its need for just one input estimate: the inverse of the covariance estimate, or the so-called precision matrix. In this paper, we propose a data-driven portfolio framework based on two regularization methods, glasso and tlasso, that provide sparse estimates of the precision matrix by penalizing its L1-norm. Glasso and tlasso rely on asset returns Gaussianity or t-Student assumptions, respectively. Simulation and real-world data results support the proposed methods compared to state-of-art approaches, such as random matrix and Ledoit-Wolf shrinkage. (C) 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
Czech name
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Czech description
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Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50200 - Economics and Business

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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