Lassance, N, DeMiguel, V and Vrins, F (2022) Optimal portfolio diversification via independent component analysis. Operations Research, 70 (1). pp. 55-72. ISSN 0030-364X
Abstract
A natural approach to enhance portfolio diversification is to rely on factor-risk parity, which yields the portfolio whose risk is equally spread among a set of uncorrelated factors. The standard choice is to take the variance as risk measure, and the principal components (PCs) of asset returns as factors. Although PCs are unique and useful for dimension reduction, they are an arbitrary choice: any rotation of the PCs results in uncorrelated factors. This is problematic because we demonstrate that any portfolio is a factor-variance-parity portfolio for some rotation of the PCs. More importantly, choosing the PCs does not account for the higher moments of asset returns. To overcome these issues, we propose to use the independent components (ICs) as factors, which are the rotation of the PCs that are maximally independent, and care about higher moments of asset returns. We demonstrate that using the IC-variance-parity portfolio helps to reduce the return kurtosis. We also show how to exploit the near independence of the ICs to parsimoniously estimate the factor-risk-parity portfolio based on Value-at-Risk. Finally, we empirically demonstrate that portfolios based on ICs outperform those based on PCs, and several state-of-the-art benchmarks.
More Details
Item Type: | Article |
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Subject Areas: | Management Science and Operations |
Additional Information: |
© 2021 INFORMS |
Funder Name: | Fonds De La Recherche Scientifique - FNRS, Belgian Federal Science Policy Office |
Date Deposited: | 15 Apr 2021 16:27 |
Date of first compliant deposit: | 12 Apr 2021 |
Subjects: |
Portfolio investment Risk |
Last Modified: | 08 Oct 2024 00:46 |
URI: | https://lbsresearch.london.edu/id/eprint/1755 |