SP500

<p>The S&amp;P 500 dataset from State Street Global Advisors with the collection period from Jan 2013 to Nov 2023.</p>

data

Bayesian estimations of a covariance matrix for multivariate
normal data. Assumes that the covariance matrix is sparse or band
matrix and positive-definite. Methods implemented include the beta-mixture
shrinkage prior (Lee et al. (2022) <doi:10.1016/j.jmva.2022.105067>),
screened beta-mixture prior (Lee et al. (2024) <doi:10.1214/24-BA1495>),
and post-processed posteriors for banded and sparse covariances
(Lee et al. (2023) <doi:10.1214/22-BA1333>; Lee and Lee (2023)
<doi:10.1016/j.jeconom.2023.105475>). This software has been developed using
funding supported by Basic Science Research Program through the National
Research Foundation of Korea ('NRF') funded by the Ministry of Education
('RS-2023-00211979', 'NRF-2022R1A5A7033499', 'NRF-2020R1A4A1018207'
and 'NRF-2020R1C1C1A01013338').

Kyeongwon Lee

bspcov

Bayesian Sparse Estimation of a Covariance Matrix

Kwangmin Lee

Kyoungjae Lee

Seongil Jo

Jaeyong Lee

SP500 function

Format

SP500 dataset — SP500

SP500 dataset

SP500: SP500 dataset

Description

Arguments

Format

Examples