Filtering time-dependent covariance matrices using time-independent eigenvalues

Christian Bongiorno (), Damien Challet and Grégoire Loeper
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Christian Bongiorno: MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec - Université Paris-Saclay
Grégoire Loeper: BNP-Paribas

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Abstract: We propose a data-driven way to clean covariance matrices in strongly nonstationary systems. Our method rests on long-term averaging of optimal eigenvalues obtained from temporally contiguous covariance matrices, which encodes the average influence of the future on present eigenvalues. This zero-th order approximation outperforms optimal methods designed for stationary systems.

Date: 2023-02-23
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Published in Journal of Statistical Mechanics: Theory and Experiment, 2023, 2023 (2), pp.023402. ⟨10.1088/1742-5468/acb7ed⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03481441

DOI: 10.1088/1742-5468/acb7ed

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