Reactive global minimum variance portfolios with k-BAHC covariance cleaning

Christian Bongiorno and Damien Challet

The European Journal of Finance, 2022, vol. 28, issue 13-15, 1344-1360

Abstract: We introduce a covariance cleaning method which works well in the very high-dimensional regime, i.e. when there are many more assets than data points per asset. This opens the way to unconditional reactive portfolio optimization when there are not enough points to calibrate dynamical conditional covariance models, which happens, for example, when new assets appear in a market. The method is a k-fold boosted version of the Bootstrapped Average Hierarchical Clustering cleaning procedure for correlation and covariance matrices. We apply this method to global minimum variance portfolios and find that k should increase with the calibration window length. We compare the performance of k-BAHC with other state-of-the-art covariance cleaning methods, including dynamical conditional covariance (DCC) with non-linear shrinkage. Generally, we find that our method yields better Sharpe ratios after transaction costs than competing unconditional covariance filtering methods, despite requiring a larger turnover. Finally, k-BAHC yields better Global Minimum Variance portfolios with long–short positions than DCC in a non-stationary investment universe.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/1351847X.2021.1963301 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Reactive Global Minimum Variance Portfolios with $k-$BAHC covariance cleaning (2023)
Working Paper: Reactive Global Minimum Variance Portfolios with $k-$BAHC covariance cleaning (2021)
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:taf:eurjfi:v:28:y:2022:i:13-15:p:1344-1360

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/REJF20

DOI: 10.1080/1351847X.2021.1963301

Access Statistics for this article

The European Journal of Finance is currently edited by Chris Adcock

More articles in The European Journal of Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().