A Bayesian Graphical Approach for Large-Scale Portfolio Management with Fewer Historical Data

Sakae Oya ()
Additional contact information
Sakae Oya: Keio University

Asia-Pacific Financial Markets, 2022, vol. 29, issue 3, No 5, 507-526

Abstract: Abstract Managing a large-scale portfolio with many assets is one of the most challenging tasks in the field of finance. It is partly because estimation of either covariance or precision matrix of asset returns tends to be unstable or even infeasible when the number of assets p exceeds the number of observations n. For this reason, most of the previous studies on portfolio management have focused on the case of $$p n$$ p > n , we propose to use a new Bayesian framework based on adaptive graphical LASSO for estimating the precision matrix of asset returns in a large-scale portfolio. Unlike the previous studies on graphical LASSO in the literature, our approach utilizes a Bayesian estimation method for the precision matrix proposed by Oya and Nakatsuma (Japanese J Stat Data Sci, 2022.) so that the positive definiteness of the precision matrix should be always guaranteed. As an empirical application, we construct the global minimum variance portfolio of $$p=100$$ p = 100 for various values of n with the proposed approach as well as the non-Bayesian graphical LASSO approach, and compare their out-of-sample performance with the equal weight portfolio as the benchmark. We also compare them with portfolios based on random matrix theory filtering and Ledoit-Wolf shrinkage estimation which were used by Torri et al. (Comput Manage Sci 16:375–400, 2019). In this comparison, the proposed approach produces more stable results than the non-Bayesian approach and the other comparative approaches in terms of Sharpe ratio, portfolio composition and turnover even if n is much smaller than p.

Keywords: Bayesian adaptive graphical LASSO; Global minimum variance portfolio; p > n problem; Positive definiteness; Precision matrix (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10690-022-09358-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:apfinm:v:29:y:2022:i:3:d:10.1007_s10690-022-09358-8

Ordering information: This journal article can be ordered from
http://www.springer.com/finance/journal/10690/PS2

DOI: 10.1007/s10690-022-09358-8

Access Statistics for this article

Asia-Pacific Financial Markets is currently edited by Jiro Akahori

More articles in Asia-Pacific Financial Markets from Springer, Japanese Association of Financial Economics and Engineering
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().