Reactive Global Minimum Variance Portfolios with $k-$BAHC covariance cleaning
Portfolio Management
2023-03-10 v2 Optimization and Control
Methodology
Abstract
We introduce a -fold boosted version of our Boostrapped Average Hierarchical Clustering cleaning procedure for correlation and covariance matrices. We then apply this method to global minimum variance portfolios for various values of and compare their performance with other state-of-the-art methods. Generally, we find that our method yields better Sharpe ratios after transaction costs than competing filtering methods, despite requiring a larger turnover.
Keywords
Cite
@article{arxiv.2005.08703,
title = {Reactive Global Minimum Variance Portfolios with $k-$BAHC covariance cleaning},
author = {Christian Bongiorno and Damien Challet},
journal= {arXiv preprint arXiv:2005.08703},
year = {2023}
}