Optimal portfolio allocation and asset centrality revisited
Optimal portfolio allocation and asset centrality revisited
This paper revisits the relationship between eigenvector asset centrality and optimal asset allocation in a minimum variance portfolio. We show that the standard definition of eigenvector centrality is misleading when the adjacency matrix in a network can take negative values. This is, for example, the case when the network topology is induced by the correlation matrix between assets in a portfolio. To correct for this, we introduce the concept of positive and negative eigenvector centrality. Our results show that the loss function associated to the minimum variance portfolio is positively/negatively related to the positive and negative eigenvector centrality under short-selling constraints but
cannot be generalized beyond that. Furthermore, in contrast to what is claimed in the related literature, this relationship does not imply any monotonic relationship between the centrality of an asset and its optimal portfolio allocation. These theoretical insights are illustrated empirically in a portfolio allocation exercise with assets from U.S. and U.K. financial markets.
Constant conditional correlation, Dynamic conditional correlation, Eigenvector centrality, Markowitz portfolio allocation, Spectral decomposition
1475-1490
Olmo, Jose
706f68c8-f991-4959-8245-6657a591056e
2021
Olmo, Jose
706f68c8-f991-4959-8245-6657a591056e
Abstract
This paper revisits the relationship between eigenvector asset centrality and optimal asset allocation in a minimum variance portfolio. We show that the standard definition of eigenvector centrality is misleading when the adjacency matrix in a network can take negative values. This is, for example, the case when the network topology is induced by the correlation matrix between assets in a portfolio. To correct for this, we introduce the concept of positive and negative eigenvector centrality. Our results show that the loss function associated to the minimum variance portfolio is positively/negatively related to the positive and negative eigenvector centrality under short-selling constraints but
cannot be generalized beyond that. Furthermore, in contrast to what is claimed in the related literature, this relationship does not imply any monotonic relationship between the centrality of an asset and its optimal portfolio allocation. These theoretical insights are illustrated empirically in a portfolio allocation exercise with assets from U.S. and U.K. financial markets.
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Optimal portfolio central final
- Accepted Manuscript
Text
Optimal portfolio allocation and asset centrality revisited
- Version of Record
More information
Accepted/In Press date: 24 May 2021
e-pub ahead of print date: 12 July 2021
Published date: 2021
Additional Information:
Funding Information:
This work was supported by project PID2019-104326GB-I00 from Ministerio de Ciencia e Innovaci?n and from Fundaci?n Agencia Aragonesa para la Investigaci?n y el Desarrollo (ARAID).
Publisher Copyright:
© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Keywords:
Constant conditional correlation, Dynamic conditional correlation, Eigenvector centrality, Markowitz portfolio allocation, Spectral decomposition
Identifiers
Local EPrints ID: 450261
URI: http://eprints.soton.ac.uk/id/eprint/450261
ISSN: 1469-7688
PURE UUID: 4cde36b6-d6cc-4f82-b126-fb2d11fd8852
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Date deposited: 19 Jul 2021 16:37
Last modified: 17 Mar 2024 03:32
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