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Reactive Global Minimum Variance Portfolios with $k-$BAHC covariance cleaning

Author

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  • Christian Bongiorno

    (MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec - Université Paris-Saclay)

  • Damien Challet

    (MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec - Université Paris-Saclay)

Abstract

We introduce a $k$-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 $k$ 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.

Suggested Citation

  • Christian Bongiorno & Damien Challet, 2021. "Reactive Global Minimum Variance Portfolios with $k-$BAHC covariance cleaning," Post-Print hal-02612262, HAL.
    • Handle: RePEc:hal:journl:hal-02612262
    DOI: 10.1080/1351847X.2021.1963301
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    References listed on IDEAS

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    1. Damien Challet, 2017. "Sharper asset ranking from total drawdown durations," Applied Mathematical Finance, Taylor & Francis Journals, vol. 24(1), pages 1-22, January.
    2. Roncalli, Thierry, 2013. "Introduction to Risk Parity and Budgeting," MPRA Paper 47679, University Library of Munich, Germany.
    3. Bouchaud,Jean-Philippe & Potters,Marc, 2003. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521819169, October.
    4. Joël Bun & Jean-Philippe Bouchaud & Marc Potters, 2017. "Cleaning large correlation matrices: tools from random matrix theory," Post-Print hal-01491304, HAL.
    5. Robert F. Engle & Olivier Ledoit & Michael Wolf, 2019. "Large Dynamic Covariance Matrices," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 363-375, April.
    6. Ester Pantaleo & Michele Tumminello & Fabrizio Lillo & Rosario Mantegna, 2011. "When do improved covariance matrix estimators enhance portfolio optimization? An empirical comparative study of nine estimators," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1067-1080.
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    Cited by:

    1. Bongiorno, Christian & Challet, Damien, 2023. "Non-linear shrinkage of the price return covariance matrix is far from optimal for portfolio optimization," Finance Research Letters, Elsevier, vol. 52(C).

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