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Article

Dynamic Portfolio Optimization with Diversification Analysis and Asset Selection Amidst High Correlation Using Cryptocurrencies and Bank Equities

by
Hamdan Bukenya Ntare
*,
John Weirstrass Muteba Mwamba
and
Franck Adekambi
School of Economics and Econometrics, University of Johannesburg, Auckland Park 2092, South Africa
*
Author to whom correspondence should be addressed.
Risks 2025, 13(6), 113; https://doi.org/10.3390/risks13060113
Submission received: 14 April 2025 / Revised: 9 June 2025 / Accepted: 12 June 2025 / Published: 16 June 2025

Abstract

There has been growing interest among investors to include cryptocurrencies in their portfolios because of their diversification potential. However, the diversification role of cryptocurrencies when added to South African bank equities is yet to be determined. This study rigorously evaluates asset co-movement and diversification benefits of integrating cryptocurrencies into South African bank equity portfolios. Using advanced financial engineering techniques, including multi-asset particle swarm optimizer (MA-PSO), random optimizer, and a static equal-weighted portfolio (EWP) model, this study analyzed the dynamic portfolio performance and diversification of cryptocurrencies in the 2017–2024 period. The portfolio performance of the three methods is also compared with the results from the traditional one-period mean–variance optimization (MVO) method. The findings underscore the superiority of dynamic models over static EWP in assessing the impact of cryptocurrency inclusion in bank equity portfolios. While pre-COVID-19 studies identified cryptocurrencies as effective hedges against market downturns, this protective role appears attenuated in the post-COVID-19 era. The dynamic MA-PSO model emerges as the optimal approach, delivering better-diversified portfolios. Consequently, South African portfolio managers must carefully evaluate investor risk tolerance before incorporating cryptocurrencies, with regulators imposing stringent guidelines to mitigate potential losses.
Keywords: asset co-movement; diversification; cryptocurrencies; PSO asset co-movement; diversification; cryptocurrencies; PSO

Share and Cite

MDPI and ACS Style

Ntare, H.B.; Muteba Mwamba, J.W.; Adekambi, F. Dynamic Portfolio Optimization with Diversification Analysis and Asset Selection Amidst High Correlation Using Cryptocurrencies and Bank Equities. Risks 2025, 13, 113. https://doi.org/10.3390/risks13060113

AMA Style

Ntare HB, Muteba Mwamba JW, Adekambi F. Dynamic Portfolio Optimization with Diversification Analysis and Asset Selection Amidst High Correlation Using Cryptocurrencies and Bank Equities. Risks. 2025; 13(6):113. https://doi.org/10.3390/risks13060113

Chicago/Turabian Style

Ntare, Hamdan Bukenya, John Weirstrass Muteba Mwamba, and Franck Adekambi. 2025. "Dynamic Portfolio Optimization with Diversification Analysis and Asset Selection Amidst High Correlation Using Cryptocurrencies and Bank Equities" Risks 13, no. 6: 113. https://doi.org/10.3390/risks13060113

APA Style

Ntare, H. B., Muteba Mwamba, J. W., & Adekambi, F. (2025). Dynamic Portfolio Optimization with Diversification Analysis and Asset Selection Amidst High Correlation Using Cryptocurrencies and Bank Equities. Risks, 13(6), 113. https://doi.org/10.3390/risks13060113

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