Does the COVID-19 pandemic affect the asset allocation performance? Evidence from a composite asset selection approach

Jung-Bin Su ()
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Jung-Bin Su: Fuzhou University of International Studies and Trade

Palgrave Communications, 2025, vol. 12, issue 1, 1-22

Abstract: Abstract This study utilizes version 6 of the regression analysis of time series (RATS) software package to implement the estimation of the bivariate diagonal generalized autoregressive conditional heteroscedasticity (GARCH) model combined with a composite asset selection approach including two hybrid performance measures to solve ‘the trade-off problem between return and risk’ and ‘the inconsistent results from different performance measures’ in the problem of asset allocation within a group of minimum variance portfolios during the pre-COVID-19 and COVID-19 periods. Empirical results show that the optimal portfolios obtained from this approach and the assets added to a portfolio to achieve better performance differ between the pre-COVID-19 and COVID-19 periods. For instance, the optimal portfolios are the Chinese yuan-Ethereum and Bitcoin-Ethereum for the pre-COVID-19 period, but the WTI-Ethereum for the COVID-19 period. To achieve better performance, we added Ethereum to our portfolio during the pre-COVID-19 period, while WTI and Bitcoin were added during the COVID-19 period. Thus, the COVID-19 pandemic had a significant impact on the performance of asset allocation in the three markets. The proposed approaches in this study can be embedded in a computer as an asset allocation algorithm of Robo-advisers.

Date: 2025
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DOI: 10.1057/s41599-025-05258-0

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