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13-06-2022

The impact of COVID-19 pandemic on the dynamic correlations between gold and U.S. equities: evidence from multifractal cross-correlation analysis

Authors: Aktham Maghyereh, Hussein Abdoh, Marcin Wątorek

Published in: Quality & Quantity | Issue 2/2023

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Abstract

This study exploits multifractal cross-correlation analysis (MFCCA) to investigate the impact of the COVID-19 pandemic on the cross-correlations between gold and U.S. equity markets using 1-min high-frequency data from January 1, 2019, to December 29, 2020. The MFCCA method shows that the pandemic caused an increase of multifractality in cross-correlations between the two markets. Specifically, the cross-correlations of small fluctuations became more persistent while those of large fluctuations became less persistent, explaining the source of multifractality. The findings of this study carry significant implications for investors, academicians, and policymakers. For example, the increase of multifractality of cross-correlation means that the non-linear relationship between gold and U.S. equity returns prevails more during economic downturns. Therefore, academicians may resort to non-linear techniques to evaluate the relationship between gold and U.S. equity markets during the health pandemic. Moreover, investors can know the value of hedging benefits over different investment time horizons during the pandemic. Finally, policymakers can better assess the economic downturns (i.e., those caused by health pandemics) over the dynamics of cross-correlation between gold and equity markets to make sound financial policies.

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The report can be accessed on this website: https://www.washingtonpost.com/business/2020/05/08/april-2020-jobs-report/).

Baur and Lucey (2010) differentiate between a haven and hedging roles. The former refers to uncorrelation or negative correlation between gold, regarded safe asset, and stocks during crises. The latter refers to uncorrelation or negative correlation during normal market conditions. Since our analysis is conducted during health crises, we use a "safe haven."

The reader can refer to Connor et al. (2015) for a literature review about the gold market and its behavioral and economic fundamental aspects.

The MF-DCCA method was developed as a combination of the multifractal detrended fluctuation analysis (MF-DFA) method of Kantelhardt et al. (2002) and the detrended cross-correlation analysis (DCCA) method proposed by Podobnik and Stanley (2008).

Among the most common multifractal cross-correlation analysis methods are the Detrended Fluctuation Analysis (DFA) of Kantelhardt et al., (2001), the Multifractal Detrended Fluctuation Analysis (MFDFA) of Kantelhardt et al. (2002), the Detrended Cross-Correlation Analysis (DCCA) of Podobnik and Stanley (2008), Multifractal Detrended Cross-Correlation Analysis (MFDCCA) of Zhou (2008), and the Multifractal Cross Wavelet Transform (MF-X-WT) analysis of Jiang et al. (2017).

We thank a reviewer for suggesting the use of the MFCCA approach.

Note that most notations and text in this section are taken from Gębarowski et al. (2019), Wątorek et al. (2019), and Li et al. (2021).

Note that the term \({F}_{xy}^{2}\left(s,v\right)\) must be a non-negative value in the MF-DFA method.

Available at https://www.dukascopy.com/swiss/english/marketwatch/historical/.

The outbreak of the COVID-19 pandemic was first identified in Wuhan, China, on December 31, 2019.

The DCC-GARCH was first proposed by Engle (2002). The model is estimated in two steps. In the first step, we compute a time-varying conditional variance using a multivariate GARCH (1, 1) process with Student's t-copulas. The time-varying correlation matrix is calculated using the standardized residuals from the first step GARCH model in the second step.

We construct dynamic hedge ratios using a rolling window analysis with out-of-sample forecasts.

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Title: The impact of COVID-19 pandemic on the dynamic correlations between gold and U.S. equities: evidence from multifractal cross-correlation analysis
Authors: Aktham Maghyereh
Hussein Abdoh
Marcin Wątorek
Publication date: 13-06-2022
Publisher: Springer Netherlands
Published in: Quality & Quantity / Issue 2/2023
Print ISSN: 0033-5177
Electronic ISSN: 1573-7845
DOI: https://doi.org/10.1007/s11135-022-01404-x

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