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Stability and similarity in financial networks—how do they change in times of turbulence?

Stability and similarity in financial networks—how do they change in times of turbulence?
Stability and similarity in financial networks—how do they change in times of turbulence?
Diversified portfolios are a key component of modern portfolio theory, based on the idea of choosing uncorrelated or unrelated stocks to minimize risk. With this in mind, we use networks to study the correlations between stocks and how this varies over time, using daily returns from the S&P500 (US), FTSE100 (UK) and DAX30 (Germany). We study both the full correlation networks and those filtered using the PMFG method. We conclude that stocks tend to become more similar in the full correlation networks during times of market disruption for the US and UK markets — implying that nodes that were once dissimilar (and therefore a good choice for a low risk portfolio) are no longer so, demonstrating the difficulties of choosing a diversified portfolio. Furthermore, these full networks are also more stable by certain measures during these periods of disruption, contrary to expectations. However, these apply less to the PMFGs and the German market.
Correlation, Finance, Networks, Portfolio selection
0378-4371
Millington, Tristan
53030837-7d43-4389-b676-1dcdabeff250
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Millington, Tristan
53030837-7d43-4389-b676-1dcdabeff250
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f

Millington, Tristan and Niranjan, Mahesan (2021) Stability and similarity in financial networks—how do they change in times of turbulence? Physica A: Statistical Mechanics and its Applications, 574, [126016]. (doi:10.1016/j.physa.2021.126016).

Record type: Article

Abstract

Diversified portfolios are a key component of modern portfolio theory, based on the idea of choosing uncorrelated or unrelated stocks to minimize risk. With this in mind, we use networks to study the correlations between stocks and how this varies over time, using daily returns from the S&P500 (US), FTSE100 (UK) and DAX30 (Germany). We study both the full correlation networks and those filtered using the PMFG method. We conclude that stocks tend to become more similar in the full correlation networks during times of market disruption for the US and UK markets — implying that nodes that were once dissimilar (and therefore a good choice for a low risk portfolio) are no longer so, demonstrating the difficulties of choosing a diversified portfolio. Furthermore, these full networks are also more stable by certain measures during these periods of disruption, contrary to expectations. However, these apply less to the PMFGs and the German market.

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Accepted/In Press date: 7 March 2021
e-pub ahead of print date: 15 April 2021
Published date: 15 July 2021
Additional Information: Funding Information: TM Acknowledges PhD studentship funding from the School of Electronics and Computer Science, University of Southampton. Publisher Copyright: © 2021 Elsevier B.V.
Keywords: Correlation, Finance, Networks, Portfolio selection

Identifiers

Local EPrints ID: 449023
URI: http://eprints.soton.ac.uk/id/eprint/449023
ISSN: 0378-4371
PURE UUID: 54bd1d7f-a1d9-42a1-8028-01e02937c389
ORCID for Mahesan Niranjan: ORCID iD orcid.org/0000-0001-7021-140X

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Date deposited: 13 May 2021 16:39
Last modified: 17 Mar 2024 06:31

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Contributors

Author: Tristan Millington
Author: Mahesan Niranjan ORCID iD

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